WO2022095067A1 - 路径规划方法、路径规划装置、路径规划系统和介质 - Google Patents

路径规划方法、路径规划装置、路径规划系统和介质 Download PDF

Info

Publication number
WO2022095067A1
WO2022095067A1 PCT/CN2020/127634 CN2020127634W WO2022095067A1 WO 2022095067 A1 WO2022095067 A1 WO 2022095067A1 CN 2020127634 W CN2020127634 W CN 2020127634W WO 2022095067 A1 WO2022095067 A1 WO 2022095067A1
Authority
WO
WIPO (PCT)
Prior art keywords
point
movable platform
auxiliary
return
position information
Prior art date
Application number
PCT/CN2020/127634
Other languages
English (en)
French (fr)
Inventor
邹亭
赵力尧
Original Assignee
深圳市大疆创新科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to CN202080073942.6A priority Critical patent/CN114746719A/zh
Priority to PCT/CN2020/127634 priority patent/WO2022095067A1/zh
Publication of WO2022095067A1 publication Critical patent/WO2022095067A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions

Definitions

  • the present application relates to the field of robotics, and in particular, to a path planning method, a path planning device, a path planning system and a medium.
  • path planning operations In the field of robotics, many typical application scenarios require path planning operations. For example, path planning of drones, transport robots, etc. in closed or open environments.
  • the related technologies cannot meet the user's personalized path planning requirements when performing path planning. For example, in the process of returning the drone, the user can only wait and cannot intervene in the returning process of the drone, and the user experience is not good.
  • the embodiments of the present application provide a path planning method, a path planning device, a path planning system, and a medium, so as to meet the user's personalized path automatic planning requirements.
  • an embodiment of the present application provides a path planning method for planning a moving path of a movable platform.
  • the method includes: first, obtaining position information of an auxiliary point in the operating environment of the movable platform, and the position of the auxiliary point. The information is generated based on the user's operation of the control device; then, a movement path of the movable platform from the return-to-home origin point to the return-to-home target point is planned based on at least the position information of the auxiliary point.
  • an embodiment of the present application provides a path planning method for planning a moving path of a movable platform.
  • the method includes: first, acquiring position information of an auxiliary point in an operating environment of the movable platform, and the position of the auxiliary point. The information is generated based on the operation of the control device by the user; then, if the position information of the auxiliary point satisfies the preset safety condition, the moving path of the movable platform to the target waypoint is planned at least based on the position information of the auxiliary point.
  • an embodiment of the present application provides a path planning apparatus for planning a moving path of a movable platform, the apparatus comprising: one or more processors; and a computer-readable storage medium for storing one or more processors
  • a computer program which, when executed by the processor, realizes: acquiring the position information of the auxiliary point in the operating environment of the movable platform, the position information of the auxiliary point is generated based on the operation of the control device by the user; The position information plans the moving path of the movable platform from the return starting point to the return destination point.
  • an embodiment of the present application provides a path planning apparatus for planning a moving path of a movable platform, the apparatus comprising: one or more processors; and a computer-readable storage medium for storing one or more processors
  • a computer program when the computer program is executed by the processor, realizes: obtains the position information of the auxiliary point in the operating environment of the movable platform, and the position information of the auxiliary point is generated based on the operation of the control device by the user; if the position of the auxiliary point is If the information satisfies the preset safety condition, the moving path of the movable platform to the target path point is planned based on at least the position information of the auxiliary point.
  • an embodiment of the present application provides a path planning system for planning a moving path, the system includes: a control device and a movable platform that are communicatively connected to each other, wherein the control device and/or the movable platform include the above Path planning device.
  • embodiments of the present application provide a computer-readable storage medium, which stores executable instructions, and when the executable instructions are executed by one or more processors, can cause one or more processors to execute the above method.
  • the user can interfere with the return path of the movable platform. If the position information of the introduced auxiliary point satisfies the preset safety condition, a movement path with higher safety can be generated based on the auxiliary point, which helps to improve the safety of the movable platform moving along the movement path.
  • 1 is an application scenario of a path planning method, a path planning device, a path planning system, and a medium provided by an embodiment of the present application;
  • FIG. 2 is an application scenario of a path planning method, a path planning device, a path planning system, and a medium provided by another embodiment of the present application;
  • FIG. 3 is a schematic flowchart of a path planning method provided by an embodiment of the present application.
  • FIG. 4 is a schematic diagram of path planning based on an auxiliary point provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of setting auxiliary points on a map displayed through an interactive interface provided by an embodiment of the present application
  • FIG. 6 is a schematic diagram of a semantic map provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a user interface for updating a semantic map provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of manually setting an obstacle area on a semantic map by a user according to an embodiment of the present application.
  • FIG. 9 is a schematic diagram of automatically updating an obstacle area on a semantic map provided by an embodiment of the present application.
  • FIG. 10 is a schematic diagram of path planning based on a semantic map and auxiliary points provided by an embodiment of the present application
  • FIG. 11 is a schematic diagram of path planning based on the respective acquisition time ordering of multiple auxiliary points according to an embodiment of the present application
  • FIG. 12 is a schematic diagram of path planning based on the positional relationship of multiple auxiliary points according to another embodiment of the present application.
  • FIG. 13 is a schematic diagram of an intermediate waypoint provided by an embodiment of the present application.
  • FIG. 14 is a schematic diagram of a safety distance provided by an embodiment of the present application.
  • 15 is a schematic diagram of a safety distance provided by another embodiment of the present application.
  • FIG. 16 is a schematic diagram of forbidding the response to the stroke when the stroke amount provided by the embodiment of the present application does not meet the safety condition
  • 17 is a schematic flowchart of a path planning method provided by another embodiment of the present application.
  • 19 is a schematic diagram of a safety distance provided by an embodiment of the present application.
  • 20 is a schematic diagram of a safety distance provided by another embodiment of the present application.
  • FIG. 21 is a schematic structural diagram of a path planning apparatus provided by an embodiment of the present application.
  • FIG. 22 is a schematic structural diagram of a movable platform provided by an embodiment of the present application.
  • return path planning is a typical application scenario. For example, the rapid return of the drone after flying out of the field of view, the return movement of the transport robot in the complex warehouse environment, etc. A major requirement of the return flight is to make the planned movement path as reasonable as possible while meeting the safety requirements.
  • the return path of a UAV (such as a consumer UAV) is automatically generated by an algorithm, and it is difficult for a user to control the intermediate state of the path.
  • the benefits of automatic path planning reduce the complexity of user implementation of path planning.
  • the automatically planned path is sometimes difficult to meet the specific needs of users.
  • the embodiment of the present application is a path planning method based on auxiliary points, which fills the technical gap that manual intervention cannot be achieved in the scenario where the return-to-home target point or the target path point has been determined and the robot automatically performs path planning.
  • the embodiment of the present application is also applicable to a stable environment where a user can conveniently intervene in the intermediate path state of the automatically planned moving path.
  • FIG. 1 is an application scenario of a path planning method, a path planning device, a path planning system, and a medium provided by an embodiment of the present application.
  • the drone can perform an automatic return-to-home operation. For example, return from the return starting point 32 (such as the current position of the drone) to the return target point 31 (such as the position where the drone is powered on).
  • the path point information provided to the planning algorithm is only the start point and the end point.
  • an auxiliary point is also provided, and the starting point, the ending point and the auxiliary point jointly describe a route desired by the user.
  • Auxiliary points enable users to participate more in the process of automatic path planning by the algorithm, such as introducing the user's preference for moving paths into path planning. For example, the user actually observes that the environment in some areas is relatively complex, and it is hoped that the robot can avoid these complex scenes.
  • the moving path automatically planned by the robot may pass through those actual high-risk areas.
  • the moving path automatically planned based on the return-to-home starting point 32 and the return-to-home target point 31 in the related art may be shown by the dotted line between the return-to-home start point 32 and the return-to-home target point 31 in FIG. 1 .
  • the UAV detects environmental information through sensors and performs automatic obstacle avoidance, so as to safely fly to the return target point 31 based on the planned moving path.
  • the planned moving path does not comprehensively consider user requirements or additional environmental information, so that the moving path cannot meet user requirements or is not an optimal return path.
  • connection line between the return origin point 32 and the return destination point 31 will pass through an area that is not suitable for flying (such as an area with woods, an area with a large lake, an area with a large number of wires, an area with a large number of birds, etc.), If you return home from these unsuitable areas, operations such as sudden braking, deceleration, course change, etc. may be triggered frequently, and it requires higher sensors for obstacle avoidance (such as omnidirectional radar, etc.), which will lead to relatively high High security risks and manufacturing costs.
  • the user hopes that the drone will pass through the designated location area during the return flight to meet specific needs (such as shooting with the drone, or detecting the temperature, humidity, illumination, etc. of the designated location area), related technologies The above requirements cannot be met.
  • movable platforms in related technologies are inseparable from complex sensors, such as real-time mapping based on lidar, ultrasonic radar and image sensors to achieve obstacle avoidance.
  • complex sensors will inevitably bring about an increase in hardware costs.
  • small robots such as small drones
  • complex sensors increase the weight of the robot and crowd out the space inside the small robot for setting energy storage media, work items, etc.
  • the related technology is based on complex hardware sensors to detect obstacles in real time to realize the planned path.
  • each robot is equipped with complex environment detection sensors.
  • complex sensors will inevitably bring about an increase in hardware costs.
  • the current path planning scheme is difficult to adapt.
  • a semantic map as a way of describing the environment can be a configuration file that can be used by multiple robotics platforms simultaneously. Since the maps loaded by the robots are the same, different robots can be guaranteed to make the same planning results under the same conditions.
  • UAVs can be consumer UAVs, agricultural UAVs, and industrial application UAVs.
  • the robot may be a road robot, an indoor robot, an aquatic robot, an underwater robot, an underwater robot, an aerial robot, etc., which is not limited herein.
  • the user can roughly describe his ideal return path by controlling the position of the auxiliary point, and then an algorithm can generate an executable return path according to the information of the auxiliary point.
  • the embodiment of the present application provides a path planning method that is convenient for manual intervention of the intermediate path state of the automatically planned moving path and is reusable.
  • the moving path can be further optimized with the help of the user's knowledge or additional environmental information for the stable environment provided by the outside, which effectively meets the various needs of the user.
  • FIG. 2 is an application scenario of a path planning method, a path planning device, a path planning system, and a medium provided by another embodiment of the present application. As shown in FIG. 2 , the working equipment mounted on the movable platform 10 will be described as an example.
  • the movable platform 10 in FIG. 2 includes a main body 11 , a carrier 13 and operating equipment (such as plant protection equipment, surveying and mapping equipment, or image capturing devices, etc.). Although the movable platform 10 is described as an aircraft, such description is not limiting and any type of movable platform previously described is applicable. In some embodiments, work equipment 14 may be located directly on movable platform 10 without the need for carrier 13 .
  • the movable platform 10 may include a power mechanism 15 , a sensing system 12 . In addition, the mobile platform 10 may also include a communication system.
  • the communication system can realize the communication between the movable platform 10 and the control device 20 having the communication system through the wireless signal 30 sent and received by the antenna 22 , and the antenna 22 is arranged on the main body 21 .
  • a communication system may include any number of transmitters, receivers, and/or transceivers for wireless communication.
  • control device 20 may provide control instructions to one or more of the movable platform 10, the carrier 13, and the work equipment, and provide control instructions from one or more of the movable platform 10, the carrier 13, and the work equipment.
  • Receive information such as obstacles, position information of auxiliary points, map information, position and/or motion information of movable platform 10, carrier 13 or operating equipment, load sensing data, such as liquid level information, flow rate information, temperature information, etc.
  • the control data of the control device 20 may include instructions regarding position, movement, braking, for the control of the movable platform 10, the carrier 13 and/or the work equipment.
  • control data may cause a change in the position and/or orientation of the movable platform 10 (eg, by controlling the power mechanism 15), or cause movement of the carrier 13 relative to the movable platform 10 (eg, by controlling the carrier 13).
  • the control data of the control device 20 can lead to load control, such as controlling the operation of the spraying equipment (starting spraying, stopping spraying, controlling flow rate, spraying angle, spraying liquid ratio, etc.).
  • the communications of the movable platform 10, the carrier 13, and/or the work equipment may include information from one or more sensors (eg, distance sensor 12, distance sensor, water level sensor, angle sensor, etc.).
  • Communication may include sensory information transmitted from one or more different types of sensors, such as GPS sensors, motion sensors, inertial sensors, proximity sensors, or image sensors.
  • the control data transmitted by the control device 20 may be used to control the state of one or more of the movable platform 10, the carrier 13 or the work equipment.
  • one or more of the carrier 13 and the work equipment may include a communication module for communicating with the control device 20 so that the control device 20 can communicate or control the movable platform 10, the carrier 13 and the work equipment individually.
  • the control device 20 may be a remote controller of the movable platform 10 , or may be an intelligent electronic device such as a mobile phone, an iPad, a wearable electronic device, etc., which can be used to control the movable platform 10 .
  • control device 20 can be far away from the movable platform 10 to realize remote control of the movable platform 10 , and can be fixedly or detachably provided on the movable platform 10 , and can be set as required.
  • the movable platform 10 may communicate with other remote devices other than the control device 20 , or with remote devices other than the control device 20 .
  • the control device 20 may also communicate with another remote device and the movable platform 10 .
  • the movable platform 10 and/or the control device 20 may be in communication with another movable platform or a carrier or payload of another movable platform.
  • the additional remote device may be a second terminal or other computing device (eg, a computer, desktop, tablet, smartphone, or other mobile device).
  • the remote device may transmit data to the mobile platform 10 (eg, transmit a semantic map), receive data from the mobile platform 10 (eg, obstacle information), transmit data to the control device 20 , and/or receive data from the control device 20 .
  • the remote device may be connected to the Internet or other telecommunications network to allow data received from the removable platform 10 and/or the control device 20 to be uploaded to a website or server.
  • the movable platform 10 may also be a land robot, an unmanned vehicle, an underwater robot, etc., which is not limited herein.
  • FIG. 3 is a schematic flowchart of a path planning method provided by an embodiment of the present application.
  • the path planning method for planning the moving path of the movable platform, may include operations S302 to S304 .
  • the position information of the auxiliary point in the operating environment of the movable platform is acquired, and the position information of the auxiliary point is generated based on the operation of the control device by the user.
  • the operating environment of the movable platform may refer to the environment in which the movable platform is located during movement, operation, and the like.
  • the environment can be open, such as an environment for outdoor plant protection operations, an environment for geological exploration, and the like.
  • the environment may be semi-enclosed, such as in a site with a factory building (eg handling, sorting, etc.).
  • the environment can be fully enclosed, such as working in a closed clean room.
  • the auxiliary point may be a virtual point, and the auxiliary point corresponds to a specific position in the operating environment, such as a two-dimensional coordinate or a three-dimensional coordinate, so that the specific position in the operating environment can be accurately located.
  • the auxiliary point may be set by means of a map or the like, eg on a map displayed by the control device.
  • the auxiliary point can also be set by means of a physical device, for example, a signal transmitting device is placed at a specific position, so that the movable platform can determine the position of the auxiliary point based on the signal transmitting device, so as to pass the position of the auxiliary point ( or a location near that auxiliary point).
  • the location information of the auxiliary point may be determined by a remote control device based on a user operation, for example, the user determines the location information of the auxiliary point by clicking, inputting coordinates, or the like.
  • the control device is provided with components such as buttons and levers, and the user can input the position information of the auxiliary point by operating these components.
  • the control device may include a display screen, and the user may input the position information of the auxiliary point through interactive components (such as virtual keys, joysticks, etc.) displayed on the display screen.
  • the user operation may also be determined and input based on gesture recognition, gesture recognition, somatosensory, or voice recognition.
  • the user may tilt the control device to control the position, direction of movement, or other aspects of the cursor on the interactive interface.
  • the tilt of the control device can be detected by one or more inertial sensors and corresponding commands (eg motion commands) are generated.
  • the user can also input operation instructions for semantic maps, loads, etc. based on user operations, for example, the operation parameters of the load (such as spraying parameters, mapping parameters, etc.) body), or any other aspect of any object on a movable platform.
  • the location information of the auxiliary point may be preset, and the auxiliary point used in this task is determined by calling a file or the like.
  • the location information of the auxiliary point is generated based on the user's manipulation of the configuration file of the control device. This not only facilitates the user to set auxiliary points, but also avoids modifying the initial information such as maps and other external information when it is necessary to locate auxiliary points with the help of external information such as maps, and improves the reuse convenience of external information such as maps.
  • a movement path of the movable platform from the return-to-home starting point to the return-to-home target point is planned based on at least the position information of the auxiliary point.
  • the user can intervene in the state of the middle path of the moving path of the movable platform from the return starting point to the return target point, which can meet various specific needs of the user, such as Personalized customization needs.
  • the location information of the return-to-home starting point may be the location information when the return-to-home task is triggered, which facilitates automatic planning of the return-to-home path.
  • the return-to-home starting point is the position of the movable platform when the return-to-home condition is triggered, and the return-to-home condition includes at least one of the following: the operation tasks (such as plant protection, exploration, freight, sorting, etc.) of the movable platform are completed;
  • the return-to-home command sent by the control device for example, the user clicks the return-to-home button on the application APP interface
  • the time when the mobile platform and the control device are disconnected from the communication connection is greater than the preset time threshold (for example, the drone signal is interrupted, interfered by the signal or exists high risk of being hijacked, etc.); the difference between the remaining power of the mobile platform’s battery and the power required for the mobile platform to return home is less than or equal to the preset power threshold.
  • the moving path is not shown by the dotted line between the home return starting point 32 and the home return target point 31 in FIG. 1 , but is shown by the solid line passing through the auxiliary point 5 in FIG. 1 .
  • the drone can bypass some areas that are not friendly to flight operations (such as forest areas, large lake areas, etc.), and improve the return safety of the drone.
  • the optimized moving path may bypass the area with many obstacles, the probability of sudden braking and changing flight direction is effectively reduced, which helps to improve the energy utilization efficiency and helps to reduce the return time.
  • it can be applied to entry-level or mobile platforms with weak obstacle avoidance capabilities or mobile platforms for stable scenarios, reducing the manufacturing cost of the mobile platform.
  • the moving path may be planned by connecting the return-to-home starting point 32 , the auxiliary point 5 and the return-to-home target point 31 .
  • the number of auxiliary points in FIG. 1 is one, but multiple auxiliary points can be set according to user requirements.
  • the auxiliary point may be determined before the path planning, or may be determined in the process of moving according to the moving path, which is not limited herein.
  • the connection method of multiple auxiliary points can be determined based on the auxiliary point connection strategy selected by the user, such as the strategy of sorting according to the time sequence of auxiliary points generation, the strategy of sorting according to the order of the current distance between the auxiliary points and the movable platform, and the strategy of sorting according to the current distance between the auxiliary points and the movable platform.
  • planning the moving path of the movable platform from the return-to-home start point to the return-to-home target point based on at least the position information of the auxiliary point may include the following operations.
  • the smooth movement path may pass through the auxiliary point or not pass through the auxiliary point.
  • the smooth moving path may pass through a range near the auxiliary point, such as a circular area with the auxiliary point as the center and the preset offset threshold as the radius.
  • FIG. 4 is a schematic diagram of path planning based on an auxiliary point according to an embodiment of the present application.
  • the planned moving path is a relatively smooth path, so by optimizing the moving path, the smoothness of the moving path can meet the maneuvering requirements of the movable platform, and the resources consumed by moving according to the moving path can be reduced, such as It can reduce the number of operations such as braking and deceleration, and reduce the consumption of energy, time and calculation.
  • the intermediate path state of the moving path obtained by the automatic planning can meet the various needs of the user for moving path planning.
  • the following is an exemplary description of determining an auxiliary point based on a user operation on the control device.
  • the location information of the auxiliary point is generated based on the user's operation on the interactive interface of the control device, and the interactive interface displays a map of the operating environment of the movable platform.
  • a map may be displayed on the interactive interface of the control device, and each coordinate (or pixel) in the map corresponds to a real space position (or area) of the operating environment of the movable platform.
  • the map may be constructed by yourself, downloaded from the Internet, or acquired by hobbyists through methods such as aerial photography, which is not limited here.
  • FIG. 5 is a schematic diagram of assisting points through map settings displayed on an interactive interface according to an embodiment of the present application.
  • the mobile platform is an unmanned aerial vehicle, and the map is imported from the outside as an example.
  • Points corresponding to the return-to-home starting point 32 and the return-to-home target point 31 may be displayed on the map, wherein the return-to-home starting point 32 may be the coordinates of the current position of the drone relative to the map.
  • the return-to-home target point 31 may be the coordinates of the location where the drone is powered on relative to the map.
  • the user sets the auxiliary point 5 on the map by clicking on a specific location on the map, or calling a file, or the like.
  • the smoothed moving path may not pass through the position of the auxiliary point, but pass through the side of the auxiliary point. For example, when the movable platform approaches the area corresponding to the current auxiliary point, the moving direction of the movable platform gradually approaches the direction of the line between the current auxiliary point and the next auxiliary point.
  • the map includes a semantic map, and the semantic information of each image area in the semantic map has a corresponding relationship with the obstacle avoidance strategy of the movable platform.
  • An exemplary description of the semantic map is given below.
  • FIG. 6 is a schematic diagram of a semantic map provided by an embodiment of the present application.
  • the semantic map can be a pixel picture (it can be in tif/tfw format), each pixel in the picture corresponds to a real-world coordinate position, and the pixel stores a semantic information corresponding to the position , marking the object type corresponding to the position.
  • a plurality of adjacent pixels with the same semantics can be collectively formed into an image area.
  • Each image region has corresponding semantic information.
  • each image area can be represented by different colors, filling patterns, etc.
  • the green pixels correspond to the semantics of farmland, indicating that the actual position corresponding to these pixels is a real object such as "farmland”.
  • the purple pixels correspond to objects like "trees”.
  • the semantic information of the image area with the origin filling pattern is a wheat field.
  • the semantic information of image regions with pure white fill patterns is rivers.
  • the semantic information of the image area with the horizontal fill pattern is the no-fly zone.
  • the semantic information of the image area with grid fill pattern is architecture.
  • the semantic information of the image region with the hatched pattern is cornfield.
  • the semantic information of the image area with the vertical line fill pattern is the high voltage line tower.
  • the granularity of the above semantic division is adjustable.
  • the granularity can be increased according to the needs, such as the wheat field and the corn field can be divided into the same category: crops; the high-voltage line tower can be incorporated into the building.
  • the granularity can be reduced according to requirements, for example, buildings can be divided into high-rise buildings and low-rise buildings.
  • the acquisition of the semantic map can include various methods, and the source of the semantic map is not limited.
  • semantic maps can come from aerial mapping recognition, manual delineation by users, third-party downloads, and the like.
  • the semantic map may include multiple image areas, and the corresponding obstacle avoidance strategies for the respective pixels in each image area are the same.
  • the semantic information corresponding to each pixel in the wheat field area is wheat field, and the obstacle avoidance strategy corresponding to the wheat field area is pass.
  • Corresponding semantic information may be set for each pixel respectively, or only corresponding semantic information may be set for each image area, which is not limited herein.
  • the correspondence between the semantic information of the image area in the semantic map and the obstacle avoidance strategy of the mobile platform can be set by the user, by the manufacturer, or by the user who draws the semantic map.
  • the above corresponding relationship can be modified by the user, such as modifying the image area in the semantic map, modifying the semantic information of the image area, modifying the obstacle avoidance strategy corresponding to the semantic information, and the like.
  • the semantic map and auxiliary points can be used as the input of path planning, and the obstacle avoidance strategy of the image region corresponding to the reference moving path can be determined based on the semantic information of each image region in the semantic map, and then the path planning can be carried out based on the obstacle avoidance strategy.
  • the obstacle avoidance strategy for the image area of the origin fill pattern and the pure white fill pattern is pass
  • the obstacle avoidance strategy for the image area of the horizontal line fill pattern and the grid fill pattern is detour
  • the obstacle avoidance strategy for the image area of the horizontal line fill pattern and the grid fill pattern is detour.
  • the obstacle avoidance strategy for the image area of the line-filled pattern is to pass over.
  • the moving path of the movable platform in a stable environment can be easily planned, instead of only relying on the sensors carried by the movable platform itself for path planning, and because the environmental information given by the semantic map is highly reliable, it is helpful to Improve the reliability of the planned path.
  • an obstacle avoidance strategy consists only of: passing and detouring.
  • the obstacle avoidance strategy includes passing, detouring, passing above, passing below, passing quickly, passing at low speed, etc., which are not limited here.
  • the path planning method provided by the embodiment of the present application has a corresponding relationship between the auxiliary points and the semantic information of each image area in the semantic map and the obstacle avoidance strategy of the movable platform, so that the movable platform can move based on the auxiliary points and the reference movement path.
  • the obstacle avoidance strategy corresponding to the passing image area is used for path planning, which can realize more reasonable and efficient path planning in complex scenes.
  • the environmental information included in the semantic map can be edited, so that the user can edit the environmental information according to the actual scene.
  • the semantic map can be modified in advance and configured according to the actual situation, which improves the flexibility of its application.
  • planning the moving path of the movable platform from the return-to-home origin point to the return-to-home target point based on at least the position information of the auxiliary point may include the following operations.
  • the target image area is determined according to the corresponding position information of the auxiliary point, the return start point, and the return target point in the semantic map.
  • the following will exemplify the determination of the target image area, the return-to-home start point, and the return-to-home target point.
  • the semantic map may be input to the movable platform or a control device of the movable platform by the user.
  • the semantic map may also be automatically downloaded by the movable platform or the control device of the movable platform, for example, searched from the semantic map collection based on the current location information of the movable platform.
  • the semantic map may also be stored locally in the movable platform or the control device of the movable platform, and automatically read from the storage space after the movable platform is powered on.
  • Semantic maps can be drawn by other electronic devices or pre-drawn by themselves.
  • the obstacle avoidance strategy includes at least one of a side detour strategy, an upper pass strategy, or a downward pass strategy.
  • the semantic map includes six image areas, wherein the semantic information of each image area is: wheat field, water surface, building, no-fly zone, cornfield, and high-voltage line tower.
  • the obstacle avoidance strategy corresponding to each image area can be: passing, high-speed passing, detouring, no flight, passing above, etc.
  • an obstacle avoidance strategy corresponding to the target image area can be determined from the semantic map based on the above-mentioned correspondence, so as to perform path planning based on the obstacle avoidance strategy.
  • the target image area may be determined according to the return-to-home initial point, the return-to-home target point, and the auxiliary point of the movable platform, the corresponding position information in the semantic map, and the semantic map. Then, according to the target image area, the semantic information of the target image area is determined.
  • the initial point and target point of returning to home can be set by the user. If the user sets the movable platform to move from position A to position B, then position A is the initial point of returning to home, and position B is the target point of returning to home.
  • the initial point of return and the target point of return can be automatically determined by the mobile platform.
  • the user sends the return command and the end operation designation to the mobile platform through the control device, or the mobile platform detects the risk of being hijacked and receives a message from air traffic control.
  • the return-to-home command is given and the preset task has been completed
  • the current position of the movable platform is used as the initial point of return-to-home
  • the initial movement path point of the movable platform is used as the return-to-home target point.
  • the starting point of the moving path is the starting point of the return home
  • the end point is the return home target point.
  • marks corresponding to auxiliary points, return-to-home starting points, and return-to-home target points can be marked on the semantic map by means of file loading, etc.
  • the marks include but are not limited to: triangles, origins, circles, crosshairs, aiming marks, and the like.
  • the auxiliary point, the return-to-home start point, and the return-to-home target point may be set by user operations, such as the user clicking on multiple positions on the semantic map, such as one or more coordinates input by the user.
  • the return-to-home starting point and the return-to-home target point can be automatically set by the movable platform, for example, the starting point coordinates when starting to return to home are used as the starting point for return-to-home, and the starting point coordinates when the movable platform starts to operate is used as the return-to-home target point.
  • the return-to-home point and return-to-home target point can be displayed on the semantic map.
  • the movement path can be planned based on the semantic information of the target image area and the outline of the target image area. For example, in a scene with a return-to-home initial point and a return-to-home target point, the connection line between the return-to-home initial point and the return-to-home target point can be determined.
  • the contour of the image area generates an alternate movement path (or waypoints) in place of the segment (or waypoints) in the line that intersect the target image area.
  • the alternative movement path may be conformal or non-conformal to at least part of the contour of the target image area. A safety distance is required between the alternate movement path and the outline of this target image area.
  • the extraction of the contour of the image region may be completed before the path planning is performed, or may be completed during the path planning process, which is not limited herein.
  • the movement path can be further optimized. For example, during the movement of the movable platform along the movement path, the following conditions should be met as much as possible: minimize triggers such as emergency stop , braking and other operating instructions, shorten the path length as much as possible, reduce energy consumption as much as possible, and improve the movement safety of the movable platform as much as possible.
  • the movement path satisfies at least one of the following conditions: the distance between the path points on the movement path and the target object is greater than the safety distance; the resource consumption of the movable platform from the initial point of the movement path to the return target point is optimal, and the resources It includes at least one of the following: path length, energy or time; the smoothness of the moving path meets the maneuvering requirements of the movable platform.
  • the safety distance may be related to the size of the movable platform, the working radius of the movable platform, etc., so as to ensure the flight safety and operation effect of the movable platform.
  • the semantic map can be updated.
  • users can update the semantic map based on their own needs, so that the updated semantic map is more in line with the user's needs or the compatibility with the current environment of the mobile platform.
  • the above method may further include the following operations.
  • an initial semantic map of the mobile platform runtime environment is obtained.
  • the update information of the semantic map generated based on the user operation is obtained.
  • the initial semantic map is updated according to the semantic map update information, so as to obtain the semantic map of the operating environment of the mobile platform.
  • the initial semantic map may be a semantic map read from a storage space, a semantic map obtained from a network, or a semantic map input by a user. This initial semantic map can be displayed in an interactive interface for editing.
  • FIG. 7 is a schematic diagram of a user interaction interface for updating a semantic map according to an embodiment of the present application.
  • the object to which the user operates may be a control device communicatively connected to the movable platform.
  • the user inputs at least one of the following information on the control device: selection information, point coordinate input information, specified operation (such as edit, delete, add), object and parameter values of the specified operation (such as coordinate value, safety distance, semantic information) , obstacle avoidance strategies), etc.
  • the control device may be integrated, for example, the remote controller is provided with a processor, a memory, a display screen, and the like.
  • the control device may be of a separate type.
  • the remote control and other electronic devices may form the control device together.
  • the remote control and the smart phone may be interconnected to form the control device.
  • an application APP
  • the smart phone may input operation instructions, set operation parameters, and the like.
  • the semantic map update information generated based on the user's operation on the user interaction interface can be acquired. In this way, it is convenient for the user to input semantic map update information to edit the semantic map.
  • the user interaction interface in FIG. 7 may include an editing area and an effect displaying area.
  • the user can input semantic map update information.
  • the semantic map update information includes location, shape, and semantic information of the updated image region in the semantic map.
  • some semantic information may not have an obstacle avoidance strategy.
  • the obstacle avoidance strategy for buildings is detour, and the corresponding relationship can be globally universal. If the user adds an image area representing the building on the semantic map, it is not necessary to create a separate The obstacle avoidance strategy is set in the image area representing the building, but its obstacle avoidance strategy is automatically set to detour based on the existing corresponding relationship.
  • the position, shape and semantic information of the existing image area at least part of the information can be edited by the user, which effectively improves the convenience of the user's operation and can be better applied to more scenes.
  • the user can update each part of the information in the editing area, such as adding a corresponding relationship, editing the corresponding relationship, or deleting the corresponding relationship.
  • you can modify the pattern (such as modifying the color, filling pattern, etc.), modify the semantic information (such as modifying the wheat field to an orchard), and modify the obstacle avoidance strategy (such as modifying the passage to detour or pass above, etc.) .
  • the semantic map update information is stored in a configuration file and can be retrieved when used. In this way, the original semantic map will not be directly modified, so that the semantic map can be reused.
  • the semantic map update information further includes an obstacle avoidance strategy corresponding to the semantic information of the updated image area in the semantic map.
  • the user can input the semantic map update information to set the obstacle avoidance strategy corresponding to the updated semantic information of the image area.
  • an obstacle avoidance strategy can be further set.
  • new semantic information is added to the map: Reef. The reef does not have a corresponding obstacle avoidance strategy, and the user needs to be prompted to set it, or there is a corresponding obstacle avoidance strategy, but it is open to User makes changes.
  • the embodiment of the present application can also modify the obstacle avoidance strategy corresponding to the semantic information of the existing image regions in the semantic map.
  • the semantic map update information includes an obstacle avoidance strategy corresponding to the semantic information of the image region in the initial semantic map.
  • FIG. 8 is a schematic diagram of manually setting an obstacle area on a semantic map by a user according to an embodiment of the present application.
  • the user can directly set the obstacle area in the semantic map according to the requirements, and the obstacle area is used to represent the virtual obstacle, so that the planned movement path can bypass the obstacle area.
  • the user can set an obstacle area at the corresponding position in the semantic map through the user interface, so that the planned path can bypass the obstacle area, which effectively improves the flexibility of operation. Spend.
  • the side detour strategy can be an obstacle avoidance strategy that is not suitable for passing from the geographic location corresponding to the image area, reducing the probability of the movable platform interfering, and reducing the occurrence of the movable platform in the process of moving according to the moving path.
  • the probability of undesired operations such as movement direction change, emergency stop, braking, etc., helps to improve movement efficiency and helps reduce energy consumption.
  • the side detour strategy includes: when the size of the target object satisfies the preset condition, adopting the first side detour strategy to perform the side detour, and when the size of the target object does not meet the preset condition, adopting the second detour strategy
  • the side detour strategy performs a side detour. For example, when the size of the target object in the target image area is too large and a similar bow-shaped moving path is adopted, if the strategy of bypassing the obstacle sideways and then continuing the operation will result in too many moving paths being used for Going around obstacles will reduce work efficiency. For another example, when the size of the target object in the target image area is small and the obstacle can be quickly bypassed, a work strategy of bypassing the obstacle can be adopted.
  • the size of the target object may refer to the maximum size of the target object, such as maximum width, maximum length, or maximum height.
  • a first side detour strategy includes moving to an adjacent work path.
  • the second side detour strategy includes detouring from the side to continue the current work path.
  • Table 1 exemplarily lists the correspondence between some semantic values and obstacle avoidance strategies in the scene where the movable platform is a UAV.
  • the concept of height information is also shown in Table 1, and the height information is exemplified below.
  • the semantic information corresponding to the graphic area indicated by the symbol 1115 is cornfield.
  • the height of cornfield is higher than that of wheatfield, for drones, it can move by passing through the top. Helps to reduce the length of the travel path by eliminating the need to detour from the side.
  • the above method may further include the following operation: acquiring the elevation information corresponding to the target image area.
  • the elevation information may be read from a semantic map with elevation information.
  • the semantic map with elevation information can be obtained by fusing the elevation map and the semantic map.
  • the semantic map with elevation information may be generated by the user marking the elevation information by himself.
  • the semantic map with elevation information may be directly generated by a mapping device with an image sensor and a ranging sensor.
  • the elevation information can be a specific height value, or a height range, etc.
  • a moving path for the movable platform to avoid the target object corresponding to the target image area may be planned according to the obstacle avoidance strategy of the movable platform corresponding to the semantic information of the target image area and the elevation information corresponding to the target image area.
  • the obstacle avoidance strategy includes passing above
  • the movable platform is planned to avoid the target object corresponding to the target image area movement path.
  • the height value of the elevation information is relative to the ground, and may also be relative to the horizontal plane, which is not limited here.
  • the height value of the elevation information may be relative to a preset plane, such as the height value of the ground plane.
  • the above method further includes: updating the semantic map based on the obstacles detected by the movable platform. For example, if it is determined that the obstacle information existing in a certain image area in the semantic map satisfies a certain condition, it can be determined that the obstacle is a relatively stable obstacle, and the semantic map can be updated according to the obstacle information.
  • FIG. 9 is a schematic diagram of automatically updating an obstacle area on a semantic map according to an embodiment of the present application.
  • an obstacle area can be set at the corresponding position on the semantic map.
  • the movable platform may also update the semantic map based on the detected obstacle information.
  • the initial semantic map may be directly modified, or an obstacle area for the semantic map may be added in the form of a configuration file.
  • whether to update the initial semantic map based on the obstacle area in the configuration file may also be determined based on the stability of the obstacle. For example, during the operation of the designated area or the process of returning home, the plant protection UAV detects the obstacle information at the same position for several consecutive times, or continuously exceeds the preset time threshold (such as 1 week, 1 month, 1 year) detected the obstacle information at the same position, the obstacle area that exists stably in the configuration file can be solidified in the initial semantic map. This enables automatic updating of the initial semantic map.
  • the obstacle area may be automatically updated by the movable platform based on preset rules, or may be set by the user. For example, before a user performs an operation, an obstacle area can be set in an area that does not require operation or needs to be avoided on the semantic map (such as an image area where there may be obstacles) to meet the diverse needs of the user.
  • FIG. 10 is a schematic diagram of route planning based on a semantic map and auxiliary points according to an embodiment of the present application.
  • the semantic information of the image area having the origin fill pattern 1111 in the semantic map 1 is a wheat field.
  • the semantic information for the image area with the pure white fill pattern 1112 is a river.
  • the semantic information of the image area with the horizontal line fill pattern 1113 is the no-fly zone.
  • the semantic information of the image area with grid fill pattern 1114 is architecture.
  • the semantic information for the image area with the diagonal hatch pattern 1115 is cornfield.
  • the semantic information of the image area with the vertical line fill pattern 1116 is the high voltage line tower.
  • the planned movement path is not a straight line between the return start point 32 and the return target point 31, nor is it a straight line between the return start point 32 and the auxiliary points 51 and 52, and between the return target point 31 and the auxiliary points 51 and 52. Instead, it is shown as a dashed line between the return-to-home start point 32 and the return-to-home target point 31 .
  • the UAV 2 can move from the position corresponding to the return start point 31 to the position corresponding to the return target point 32 according to the planned movement path.
  • the moving path bypasses the image area of the horizontal line filling pattern 1113, and the obstacle avoidance strategy corresponding to this area is a detour strategy.
  • the moving path passes through the image area of the pure white fill pattern 1112, and the obstacle avoidance strategy corresponding to this area is pass.
  • the movement path passes near the auxiliary point 52 to meet the specific needs of the user. Passing above the moving path passes through the image area of the oblique line filling pattern 1115, and the obstacle avoidance strategy corresponding to this area is to pass above.
  • the moving path does not pass near the auxiliary point 51 , because the area where the auxiliary point 51 is located is the image area of the vertical line filling pattern 1116 , and the obstacle avoidance strategy corresponding to this area is detour to improve the flight safety of the UAV 2 .
  • the moving path has been smoothed, so that when the UAV 2 moves along the moving path, it can move with as little deceleration as possible to meet the maneuvering requirements.
  • the number of auxiliary points is multiple.
  • the above method may further include: sorting the plurality of auxiliary points.
  • the auxiliary points can be sorted based on the auxiliary point connection strategy, and different auxiliary point connection strategies correspond to different sorting algorithms.
  • the auxiliary points can be sorted for one indicator or multiple indicators. Indicators include, but are not limited to: generation time of auxiliary points, distance between auxiliary points and specified points, length of moving paths planned according to the ordering, moving time of the moving paths planned according to the ordering, energy consumption of the moving paths planned according to the ordering Wait.
  • connecting the return origin point, auxiliary point and return target point to obtain the reference movement path may include the following operations: connecting the return start point, multiple auxiliary points and return destination points in order to obtain the reference movement path.
  • ordering the plurality of auxiliary points may include: ordering the auxiliary points in a time sequence in which the plurality of auxiliary points are acquired.
  • FIG. 11 is a schematic diagram of path planning based on the respective acquisition time ordering of multiple auxiliary points according to an embodiment of the present application.
  • the acquisition time of the auxiliary point 52 is earlier than the acquisition time of the auxiliary point 51. Therefore, the return starting point 32 and the auxiliary point 52 are connected, and the auxiliary point 52 and the auxiliary point 51 are connected. 51 and the return target point 31 are connected. It should be noted that only two auxiliary points are shown in FIG. 11 , and there may be more or less auxiliary points, which are not limited here.
  • the moving path in Fig. 11 has not been smoothed. In order to meet the maneuvering requirements such as the flight of an unmanned aerial vehicle, the moving path can be smoothed. In addition, it is inevitable that the user will make a mistake or want to cancel the previously set auxiliary point. The user can operate the set auxiliary point by pressing buttons such as "Cancel" and "Delete" on the APP display interface.
  • multiple auxiliary points and target points can be connected in order to obtain multiple sequentially connected sub-reference moving paths, and then the moving path of the movable platform can be planned based on the multiple sequentially connected sub-reference moving paths.
  • sorting the multiple auxiliary points may include: sorting the multiple auxiliary points according to the relative positional relationship between the multiple auxiliary points and the return-to-home starting point or the return-to-home target point.
  • FIG. 12 is a schematic diagram of route planning based on the positional relationship of multiple auxiliary points according to another embodiment of the present application.
  • the distance between the auxiliary point 52 and the return starting point 32 is greater than the distance between the auxiliary point 51 and the return starting point 32. Therefore, the return starting point 32 and the auxiliary point 51 are connected.
  • the auxiliary point 52 and the auxiliary point 51 are connected, and the auxiliary point 52 and the return target point 31 are connected. Same as above, only two auxiliary points are shown in FIG. 11 , and there may be more or less auxiliary points, which is not limited herein.
  • the moving path in Figure 11 can also be smoothed. This helps to reduce the length of the moving path.
  • an auxiliary point may also be set or updated.
  • the temporary auxiliary point may be acquired first, and then the moving path of the movable platform is updated based on the auxiliary point, the temporary auxiliary point and the target point.
  • a temporary auxiliary point is acquired, and the temporary auxiliary point is used as the next auxiliary point relative to the current auxiliary point among the plurality of auxiliary points.
  • the temporary auxiliary point is used as the auxiliary point between the two auxiliary points closest to the temporary auxiliary point among the multiple auxiliary points, so as to determine the respective sequence of the multiple auxiliary points and the temporary auxiliary point.
  • the temporary auxiliary point is used as the next auxiliary point of the last passing auxiliary point to determine the respective ordering of the plurality of auxiliary points and the temporary auxiliary point. This makes it possible to update the movement path of the movable platform based on at least the respective sequential order of the plurality of auxiliary points and the temporary auxiliary points.
  • the target image area may be first determined according to the position of the auxiliary point, and an intermediate point of the moving path is found in the target image area, so as to perform path planning based on the intermediate point. Accordingly, planning the moving path of the movable platform from the return-to-home origin point to the return-to-home target point based on at least the position information of the auxiliary point may include the following operations.
  • the target three-dimensional area where the movement path is located is determined in the operating environment of the movable platform based on at least the position information of the auxiliary point.
  • an intermediate waypoint is determined in the target three-dimensional area, so as to plan a moving path of the movable platform from the return-to-home starting point via the intermediate waypoint to the return-to-home target point.
  • intermediate waypoints can be determined in the target 3D region by optimizing the target loss function.
  • the return-to-home starting point, the auxiliary point, and the return-to-home target point can be connected, and the target three-dimensional area can be determined based on the connection.
  • the target three-dimensional area can be determined based on the connection.
  • a pipe-shaped target three-dimensional region can be formed by using this line as the central axis.
  • determining the intermediate waypoints in the target three-dimensional region may include the following operations: optimizing the target loss function to determine motion parameters of the intermediate waypoints, where the motion parameters of the intermediate waypoints at least include position parameters.
  • speed parameters, acceleration parameters, etc. may also be included.
  • optimizing the target loss function to determine the moving path of the movable platform to avoid the target object may include: minimizing the target loss function to determine the position parameters of the movable platform corresponding to multiple target trajectory points, The position parameter of the mobile platform minimizes the function value of the objective loss function.
  • the objective loss function may include at least one of the following: a collision cost function for constraining the distance between waypoints and obstacles on the moving path.
  • the objective loss function can also include an auxiliary point cost function, which is used to constrain the distance between the path point and the auxiliary point on the moving path.
  • the objective loss function may also include a path length cost function, which is used to constrain the total length of the moving path.
  • the objective loss function can also include kinematic and dynamic cost functions to ensure that the obtained moving path is an executable moving path of the movable platform.
  • the cost function shown above is only an example, and should not be construed as a limitation on the present application.
  • corresponding cost functions can be set for various parameters that can affect the path planning.
  • FIG. 13 is a schematic diagram of an intermediate waypoint provided by an embodiment of the present application.
  • a plurality of intermediate waypoints are determined in the target three-dimensional area, so that a plurality of intermediate waypoints can be connected to generate a movement path for the target three-dimensional area.
  • planning the moving path of the movable platform from the return-to-home starting point to the return-to-home target point based on at least the position information of the auxiliary point may include: if the position information of the auxiliary point satisfies a preset safety condition, at least The position information plans the moving path of the movable platform from the return starting point to the return destination point.
  • the auxiliary point when it auxiliary point satisfies the preset safety conditions, it is helpful to improve the safety of the movable platform when it moves according to the moving path. For example, the auxiliary point will not cause the movable platform to interact with obstacles or obstacle areas. put one's oar in.
  • the user interface displays a semantic map
  • the preset safety conditions include, but are not limited to, at least one of the following: the auxiliary point is not set in an area where passage is prohibited (such as no-fly, air control, traffic control, etc.), and the auxiliary point is not set in the semantic In the obstacle area in the map, the auxiliary point is not set in the area where the obstacle avoidance strategy is the detour strategy in the semantic map, etc.
  • the above method may further include the following operation: if the position information of the auxiliary point does not meet the preset safety condition, updating the position information of the auxiliary point, so as to plan the movable platform from returning home based on at least the position information of the auxiliary point The movement path from the start point to the return target point.
  • the position information of the auxiliary point can be modified so that the modified position information of the auxiliary point satisfies the preset safety condition.
  • the updated auxiliary point is an optimal auxiliary point for a preset index and meets a safety condition
  • the preset index includes at least one of the following: distance, energy consumption or path length.
  • the two points closest to the auxiliary point to be updated (which can be two points in the auxiliary point, the return starting point, the return target point, etc.) can be connected to obtain a connection. Then, through the auxiliary point to be updated, make the vertical line of the above-mentioned connecting line, and select the position closest to the auxiliary point to be updated and meet the safety distance from the vertical line to update the position information of the auxiliary point.
  • the above method may further include the following operation: if the position information of the auxiliary point does not meet the preset safety condition, deleting the position information of the auxiliary point. In this way, the risks in the process of moving the movable platform according to the moving path can be simply and effectively reduced.
  • the image area labeled 1116 represents the high-voltage line tower, the corresponding obstacle avoidance strategy is the detour strategy, and the auxiliary point 51 is set in this area.
  • the auxiliary point 51 In order to reduce the flight safety risk of the drone, it can be deleted directly Or ignore the auxiliary point 51, and at the same time, in order to facilitate the user to understand the reason why the planned moving path does not pass through the auxiliary point 51 (or near it), prompt information can be displayed in the interactive interface, such as the auxiliary point 51 is set in a dangerous area and has been deleted. Auxiliary point 51.
  • the preset safety condition may include: the distance between the auxiliary point and the obstacle closest to the auxiliary point is greater than a preset safety distance threshold.
  • the obstacle may be a physical obstacle or a virtual obstacle, such as an obstacle area or an electronic fence area selected by a user that needs to be bypassed.
  • the obstacle avoidance strategy further includes safety distance information, and the safety distance information may be used to indicate the minimum distance between the movable platform and the target object corresponding to the target image area.
  • image regions with different semantic information can each have different safety distances, so as to reduce the length of the movement path on the basis of ensuring movement safety.
  • a larger safety distance can be set for the image area representing the building in the semantic map, such as increasing the value of the safety distance corresponding to the semantic value.
  • the electromagnetic radiation generated by the electric wire may cause greater interference to the communication between the control device and the movable platform. Therefore, a larger image area can be set for the image area representing the electric wire in the semantic map. safe distance.
  • the safety distance is related to at least one of the following: the size of the movable platform, and the working radius of the movable platform.
  • the obstacle avoidance strategy contains the safety distance information
  • the obstacle avoidance strategy is related to the semantic information, so that the correspondence between the safety distance information and the semantic information can be easily determined.
  • the braking distance of the road robot at high speed is greater than the braking distance of the road robot at low speed.
  • the braking distance of the aerial robot The distance is greater than the braking distance of the road robot, etc. Therefore, the safety distance can be set based on the minimum obstacle avoidance distance of the movable platform, so as to improve the safety of the movable platform.
  • FIG. 14 is a schematic diagram of a safety distance provided by an embodiment of the present application.
  • FIG. 15 is a schematic diagram of a safety distance provided by another embodiment of the present application.
  • the safety distance may be a distance for two scenarios, as shown by the bidirectional arrow line segment in the reference figure.
  • the safety distance shown in Figure 14 is for the graphical area where the obstacle avoidance strategy in the semantic map is detour.
  • the movable platform detours the area corresponding to a certain graphical area, the distance between the movable platform and the area The distance needs to be greater than the safe distance.
  • the safety distance shown in Figure 15 is for the detected obstacle in the process of moving the movable platform according to the planned moving path, and it is necessary to control the distance between the movable platform and the obstacle to be greater than the safety distance.
  • the movable platform may move based on a planned movement path.
  • obstacle avoidance needs to be performed based on the real-time detected obstacle information.
  • the complexity of the sensor adopted in this embodiment can be greatly reduced.
  • the technical solution of the present application can only use two-way radar, which can reduce hardware costs. At the same time, it also reduces the body weight, computing resource consumption and energy consumption.
  • the above method may further include the following operations: controlling the movable platform
  • the platform moves based on the moving path and the obstacle information detected by the movable platform through the sensors.
  • the mobile platform detects the obstacle information through the sensor, and can use the method of detecting obstacles in related technologies, such as detection based on image, radar (such as lidar or ultrasonic radar, etc.), ranging sensor, etc., which is not limited here. .
  • controlling the movable platform to move based on the movement path and the obstacle information detected by the movable platform through the sensor may include: when the confidence of the obstacle detected by the sensor is greater than a preset threshold, controlling the movable platform The platform moves based on the moving path and the obstacle information detected by the movable platform through the sensor.
  • the confidence of the obstacle is related to the number of times the obstacle is repeatedly detected and the environmental information when the obstacle is detected.
  • the confidence of the obstacle is less than a certain threshold, it is determined that the information of the obstacle is unreliable and can be ignored. For example, in windy and rainy weather, information about obstacles such as leaves and raindrops may be detected, but the confidence of these obstacles is low. If the detection results in multiple adjacent detection cycles are quite different, the obstacle can be ignored. information. For example, if the UAV detects an obstacle at the same location multiple times or the UAV detects an obstacle continuously in a small area, the confidence of the obstacle information is high.
  • a geo-fence-like effect can also be achieved based on auxiliary points and/or semantic maps, which facilitates setting operational specifications for the movable platform operator and reduces the risk of the movable platform moving to a restricted area.
  • the control lever amount generated based on the user operation is received. If it is determined that the lever amount will cause the movable platform to enter the target image area (eg, the graphics area corresponding to the obstacle avoidance strategy is a detour strategy) and/or away from the next auxiliary point relative to the movement path, the lever amount is not responded to.
  • the target image area eg, the graphics area corresponding to the obstacle avoidance strategy is a detour strategy
  • a closed no-fly zone can be set up through a semantic map, or an auxiliary point located outside the no-fly zone, or a no-fly zone can be set for a specific area in the competition venue to avoid drone operations Improperly causing harm to spectators, etc., or participating in the competition by illegal means, etc.
  • FIG. 16 is a schematic diagram of forbidding the response to the stroke when the stroke amount provided by the embodiment of the present application does not meet the safety condition.
  • the dotted line is the movement track of the movable platform
  • the peripheral grid area is set as the semantic information is a building
  • a no-fly zone is also set inside. For example, if the user's lever amount would cause the movable platform to enter a graphics area corresponding to a building or a graphics area corresponding to a no-fly zone, the movable platform may determine, based on the semantic map, not to respond to that lever amount.
  • the movable platform would determine, based on the semantic map, not to respond to that lever amount, which could be based on the auxiliary point for no Human-machine operation for guidance is especially suitable for high-risk areas as shown in Figure 16.
  • the guidance effect can be improved by setting multiple auxiliary points.
  • FIG. 17 is a schematic flowchart of a path planning method provided by another embodiment of the present application.
  • the process of path planning can mainly include three parts: input condition preparation, algorithm planning, and execution. The specific content of each stage is introduced in turn.
  • the input conditions are some parameters pre-set by the operator for the return-to-home task.
  • the task of returning to home is to safely return to the target point from the current position of the robot, so it is necessary to pre-set the start and end points of the return home.
  • the starting point of the return flight is the current position of the robot, and the end point of the return flight can be set through the default origin (home point), or the user can click to set through the app, or input it in the form of a configuration file.
  • the technical solution of this application is not limited.
  • the auxiliary point position setting can be shown in the following two ways. For example, the user clicks on each auxiliary point in turn on the interactive interface and adjusts its position. For another example, the user modifies the setting of the auxiliary point in the form of a configuration file.
  • detour obstacle information is set (this operation is optional).
  • the user can preset the area to be detoured through this operation, or it can be detected by the robot in real time.
  • the planning parameters include but are not limited to: the minimum safe distance of the robot from the obstacle, the robot motion limit parameters, the flying height of the robot, and the like.
  • the planning map is a storage structure inside the algorithm, which saves the data calculated by the user planning algorithm. For example, some known environmental information can be loaded into the algorithm, at the same time, for real-time planning scenarios, obstacles can also be detected by the robot's sensors, and then the obstacle information can be loaded into the planning map, and then the generated path can be planned.
  • the auxiliary point can be a rough shape that defines the planned path, and generally the generated route will pass near the auxiliary point. Since it is set by the user, it is inevitable to coincide with the actual obstacle information, that is, the auxiliary points are within the safe radius of the obstacle. If these auxiliary points are introduced into the planning, the final generated route is bound to be more dangerous. Therefore, it is necessary to filter the unsafe auxiliary points. For example, the following two processing methods can be adopted: for example, the unsafe auxiliary points are directly deleted. For example, look for an alternate auxiliary point around an unsafe auxiliary point.
  • auxiliary point 3 is in the semantic map in the graphics area corresponding to the speech "building", so the auxiliary point (3) is deleted.
  • route planning there are four reference points for route planning in ⁇ 0, 1, 2, 4 ⁇ , with a total of 3 route planning segments: [0,1][1,2][2,4]. Carry out path planning for the above three segments respectively to obtain three routes, and then connect the three routes in turn to form the final return route. Further, the three-segment route can be smoothed.
  • the path needs to be properly formatted (for example, the moving path is processed into a data format that can be read by a mobile platform), so that it meets the requirements of later execution, and then the path is output.
  • the actuator of the UAV acquires the movement path and executes the movement path.
  • the following takes the drone and its control device as an example to illustrate the execution subject of the above operations. Among them, at least part of the following information can be mutually transmitted between the UAV and its control device.
  • the location information of the auxiliary points can be obtained by the drone and/or its control device.
  • Whether the return-to-home condition is triggered may be determined by the drone and/or its controls.
  • a semantic map of the operating environment of the mobile platform can be obtained by the UAV and/or its controls.
  • the semantic information of the target image area in the semantic map can be determined by the drone and/or its control device.
  • Multiple assistance points may be sequenced by the drone and/or its controls.
  • the location information of the auxiliary points may be updated by the drone and/or its controls.
  • Auxiliary points can be deleted by the drone and/or its controls.
  • the movement path of the movable platform from the return-to-home origin point to the return-to-home target point can be planned by the UAV and/or its control device.
  • the semantic map update information may be received by the control device.
  • a user interface and various information related to path planning can be displayed by the control device.
  • the obstacle information during the flight can be detected by the drone through the sensor.
  • the semantic map can be updated by the drone and/or its controls.
  • User actions may be received by the control device to generate lever quantities.
  • each of the above operations is only an exemplary description, and should not be construed as a limitation of the present application. It may be independently completed by one of the movable platform, the control device, the pan/tilt or the load, or several of them may cooperate with each other. Finish.
  • a human-computer interaction module such as a display for displaying a human-computer interaction interface, etc.
  • the user can directly display the interactive interface on the movable platform.
  • independent completion includes actively or passively, directly or indirectly obtaining corresponding data from other devices to perform corresponding operations
  • the path planning method provided by the embodiment of the present application improves the user's degree of freedom in editing the moving path.
  • the moving path generated by the user in the background better reflects the user's intention in the form of setting auxiliary points.
  • the introduction of experience and external knowledge into the path planning process provides a feasible solution for path planning under complex terrain, achieving a balance between automated planning and manual planning, and a small manual workload brings great efficiency promote.
  • the embodiment of the present application can reduce the hardware cost to a certain extent. Obviously, if the user's auxiliary point is reasonable enough, the robot does not need or only needs to configure a small amount of expensive hardware devices such as sensors for detecting obstacles.
  • the path planning method provided by the embodiments of the present application uses the environmental information provided by auxiliary points and semantic maps as at least part of the basis for path planning, which enriches the sources of environmental information and reduces the dependence on related technologies to perceive environmental information through complex sensors.
  • the semantic map can be reused, and there is no need to perceive the environment information through complex sensors to build the map in real time every time the path planning is performed.
  • the environmental information included in the auxiliary point and the semantic map can be edited, the user can edit the environmental information according to the actual scene, which improves the flexibility of its application.
  • the semantic map since the semantic map is pre-made, the calculation amount of the environment detection during the operation of the mobile platform is reduced, and the resource consumption is effectively reduced.
  • Another aspect of the present application provides a path planning method for planning a moving path of a movable platform.
  • FIG. 18 is a schematic flowchart of a path planning method provided by another embodiment of the present application.
  • the method may include operations S1802 to S1804.
  • a movement path of the movable platform to move to the target waypoint is planned at least based on the position information of the auxiliary point.
  • the target waypoint may be a waypoint to which the user expects the movable platform to move, such as a return-to-home target point, etc., which will not be repeated here.
  • the path planning method provided by the embodiment of the present application provides a solution for planning the moving path of the movable platform to the target path point based on at least the position information of the auxiliary point when the auxiliary point satisfies the preset safety condition, which can effectively improve the planned movement path security.
  • the preset safety conditions include but are not limited to: the distance between the auxiliary point and the obstacle closest to the auxiliary point is greater than the preset safety distance threshold.
  • the obstacle may be a physical obstacle or a virtual obstacle, such as a user-selected obstacle detour area or an electronic fence.
  • FIG. 19 is a schematic diagram of a safety distance provided by an embodiment of the present application.
  • the safety distance is for the detected obstacle in the process of moving the movable platform according to the planned movement path, and it is necessary to control the distance between the movable platform and the obstacle to be greater than the safety distance.
  • a movable platform can move based on a planned movement path.
  • obstacle avoidance needs to be performed based on the real-time detected obstacle information.
  • the complexity of the sensor adopted in this embodiment can be greatly reduced.
  • the technical solution of the present application can only use two-way radar, which can reduce hardware costs. At the same time, it also reduces the body weight, computing resource consumption and energy consumption.
  • FIG. 20 is a schematic diagram of a safety distance provided by another embodiment of the present application.
  • the safety distance can be shown as a double-headed arrow line segment in the figure.
  • the safety distance shown in FIG. 20 is the distance between the auxiliary point 52 and the auxiliary point 52 in which the obstacle avoidance strategy in the semantic map is detoured
  • the distance between zones needs to be greater than the safe distance threshold.
  • the above method further includes: if the position information of the auxiliary point does not meet the preset safety condition, updating the position information of the auxiliary point, so as to plan the movable platform to move to the target path based on the updated position information of the auxiliary point The movement path of the point.
  • planning the moving path of the movable platform to the target waypoint based on at least the position information of the auxiliary point includes: if the position information of the auxiliary point satisfies the preset safety condition condition, the moving path of the movable platform from the starting waypoint to the target waypoint is planned based on the position information of the auxiliary point.
  • the starting waypoint is the position point of the movable platform when the return-to-home condition is triggered
  • the return-to-home condition includes at least one of the following: the operation task of the movable platform is completed; the movable platform obtains the return-to-home instruction sent by the control device; The time when the mobile platform is disconnected from the control device is greater than the preset time threshold; the difference between the remaining power of the mobile platform's battery and the power required for the mobile platform to return home is less than or equal to the preset power threshold.
  • the location information for the auxiliary point is generated based on user manipulation of a configuration file of the control device.
  • the location information of the auxiliary point is generated based on the user's operation on the interactive interface of the control device, and the interactive interface displays a map of the operating environment of the movable platform.
  • the map includes a semantic map, and the semantic information of each image area in the semantic map has a corresponding relationship with the obstacle avoidance strategy of the movable platform.
  • planning the movement path of the movable platform to the target waypoint based on at least the position information of the auxiliary point includes: according to the auxiliary point and the target waypoint in the semantic map The corresponding position information in the target image area is determined; at least based on the position information of the auxiliary point and the semantic information of the target image area corresponding to the obstacle avoidance strategy of the movable platform, the moving path of the movable platform to the target waypoint is planned.
  • the obstacle avoidance strategy includes at least one of the following: a detour strategy, passing above or passing below.
  • the moving path is obtained by smoothing the reference moving path, and the smoothness of the moving path meets the maneuvering requirements of the movable platform.
  • the number of auxiliary points is multiple.
  • the method further includes: sorting a plurality of auxiliary points; if the position information of the auxiliary points satisfies the preset safety condition, connecting the auxiliary point and the target path point, and obtaining the reference moving path includes: if the position information of the auxiliary points satisfies the preset safety condition, connecting the auxiliary point and the target path point If the safety conditions are preset, at least one auxiliary point and the target path point are connected in order to obtain a reference moving path.
  • sorting the multiple auxiliary points includes: sorting the auxiliary points according to the time sequence in which the multiple auxiliary points are obtained; or sorting the multiple auxiliary points according to the relative positional relationship between the multiple auxiliary points and the target waypoint. sort.
  • planning the movement path of the movable platform to the target waypoint based on at least the position information of the auxiliary point may include the following operations.
  • determining the intermediate waypoints in the target three-dimensional region may include: optimizing a target loss function to determine motion parameters of the intermediate waypoints, where the motion parameters of the intermediate waypoints include at least a position parameter.
  • FIG. 21 is a schematic structural diagram of a path planning apparatus provided by an embodiment of the present application.
  • the path planning apparatus 2100 may include one or more processors 2110, and the one or more processors 2110 may be integrated into one processing unit, or may be separately arranged in multiple processing units.
  • the computer-readable storage medium 2120 is used for storing one or more computer programs 2121, and when the computer programs are executed by the processor, the above path planning method is implemented.
  • a computer program when executed by a processor, implements the following operations.
  • the position information of the auxiliary point in the operating environment of the movable platform is acquired, and the position information of the auxiliary point is generated based on the operation of the control device by the user.
  • a moving path of the movable platform from the return-to-home starting point to the return-to-home target point is planned based on at least the position information of the auxiliary point.
  • the position information of the auxiliary point in the operating environment of the movable platform is obtained, and the position information of the auxiliary point is generated based on the operation of the control device by the user.
  • a movement path for the movable platform to move to the target waypoint is planned at least based on the position information of the auxiliary point.
  • the path planning apparatus 2100 may be set in one execution body or respectively set in multiple execution bodies.
  • the path planning device 2100 can be set in the land robot.
  • a display screen is arranged on the body to facilitate interaction with the user.
  • at least part of the path planning device 2100 can be provided in the control device, such as the relevant functions for accepting user operations are provided in the control device.
  • At least a part of the path planning apparatus 2100 may be set in a movable platform, such as at least one of an information transmission function, an environmental information sensing function, and a linkage control function.
  • at least a part of the path planning apparatus 2100 may be provided in a load, such as performing a related function of a job, and the like.
  • the processing unit may comprise a Field-Programmable Gate Array (FPGA) or one or more ARM processors.
  • the processing unit may be connected to the non-volatile computer readable storage medium 2120 .
  • the non-volatile computer-readable storage medium 2120 may store logic, code, and/or computer instructions executed by the processing unit for performing one or more steps.
  • the non-volatile computer-readable storage medium 2120 may include one or more storage units (removable media or external memory such as SD card or RAM).
  • the data sensed by the sensor may be transferred and stored directly into a storage unit of the non-volatile computer-readable storage medium 2120 .
  • the storage units of the non-volatile computer-readable storage medium 2120 may store logic, code, and/or computer instructions executed by the processing unit to perform various embodiments of the various methods described herein.
  • a processing unit may be configured to execute instructions to cause one or more processors of the processing unit to perform the tracing functions described above.
  • the storage unit may store sensing module sensing data, the data sensing being processed by the processing unit.
  • the storage unit of the non-volatile computer-readable storage medium 2120 may store processing results generated by the processing unit.
  • the processing unit may be connected to the control module for controlling the state of the movable platform.
  • the control module may be used to control the power mechanism of the movable platform to adjust the spatial orientation, velocity and/or acceleration of the movable platform relative to six degrees of freedom.
  • the control module may control one or more of the carrier, load or sensing module.
  • the processing unit may also be connected to the communication module for transmitting and/or receiving data with one or more peripheral devices (eg, terminals, display devices, or other remote control devices).
  • peripheral devices eg, terminals, display devices, or other remote control devices.
  • Any suitable communication method may be utilized here, such as wired communication or wireless communication.
  • the communication module may utilize one or more local area networks, wide area networks, infrared, radio, Wi-Fi, peer-to-peer (P2P) networks, telecommunication networks, cloud networks, and the like.
  • P2P peer-to-peer
  • a relay station such as a signal tower, a satellite, or a mobile base station, can be used.
  • the above-mentioned various components may be compatible with each other.
  • one or more components are located on a movable platform, carrier, payload, terminal, sensing system, or additional external device in communication with each of the foregoing.
  • one or more of the processing unit and/or non-transitory computer-readable medium may be located in different locations, such as on a removable platform, carrier, payload, terminal, sensing system, or Additional external devices that communicate with the foregoing devices and various combinations of the foregoing.
  • control device adapted to the movable platform may include an input module, a processing unit, a memory, a display module, and a communication module, all of which are connected by a bus or similar network.
  • the input module includes one or more input mechanisms to obtain input generated by the user by manipulating the input module.
  • Input mechanisms include one or more joysticks, switches, knobs, slide switches, buttons, dials, touchscreens, keypads, keyboards, mice, voice controls, gesture controls, inertial modules, and the like.
  • the input module may be used to obtain user input for controlling the movable platform, carrier, load, or any aspect of the components therein. Any aspect includes attitude, position, orientation, flight, tracking, etc.
  • the input mechanism may be that the user manually sets one or more positions, each position corresponding to a preset input, to control the movable platform.
  • the input mechanism may be operated by a user to input control commands to control the movement of the movable platform.
  • a user can use a knob, switch, or similar input mechanism to input a motion mode of the movable platform, such as auto-flying, auto-pilot, or moving according to a preset motion path.
  • the user may control the position, attitude, orientation, or other aspects of the movable platform by tilting the control device in some way.
  • the tilt of the control device can be detected by one or more inertial sensors, and corresponding motion commands can be generated.
  • the user may utilize the input mechanisms described above to adjust operational parameters of the payload (eg, zoom), the attitude of the payload (via the carrier), or other aspects of any object on the movable platform.
  • the input mechanism may be operated by the user to input the aforementioned descriptive object information.
  • the user may select an appropriate tracking mode, such as a manual tracking mode or an automatic tracking mode, using a knob, switch, or similar input mechanism.
  • the user may also utilize this input mechanism to select a specific target to be tracked, target type information to execute, or other similar information.
  • the input module may be executed by more than one device.
  • the input module can be implemented by a standard remote controller with a joystick.
  • a standard remote controller with a joystick connects to a mobile device (eg, a smartphone) running a suitable application (“APP”) to generate control commands for the movable platform.
  • APPs can be used to obtain user input.
  • the processing unit may be connected to the memory.
  • Memory includes volatile or non-volatile storage media for storing data, and/or logic, code, and/or program instructions executable by a processing unit for performing one or more rules or functions.
  • the memory may include one or more storage units (removable media or external memory such as SD card or RAM).
  • the data input to the module may be directly transferred and stored in a storage unit of the memory.
  • the storage units of the memory may store logic, code and/or computer instructions executed by the processing unit to perform various embodiments of the various methods described herein.
  • the processing unit may be configured to execute instructions to cause one or more processors of the processing unit to process and display sensory data (eg, images) obtained from the movable platform, control commands generated based on user input, including motion commands and objects information, and cause the communication module to transmit and/or receive data, etc.
  • the storage unit may store sensed data or other data received from an external device such as a removable platform.
  • the storage unit of the memory may store the processing result generated by the processing unit.
  • the display module can be used to display the position, translation velocity, translation acceleration, direction, angular velocity, angular acceleration, or a combination thereof of the movable platform 10, the carrier 13 and/or the working equipment as shown in FIG. Information.
  • the display module can be used to obtain information sent by the movable platform and/or payload, such as sensory data (images recorded by cameras or other image capture devices), described tracking data, control feedback data, and the like.
  • the display module may be executed by the same device as the input module. In other embodiments, the display module and the input module may be executed by different devices.
  • the communication module may be used to transmit and/or receive data from one or more remote devices (eg, removable platforms, carriers, base stations, etc.).
  • the communication module can transmit control signals (such as motion signals, target information, tracking control commands) to peripheral systems or devices, such as the movable platform 10, the carrier 13 and/or the operation equipment 14 in FIG. 2 .
  • the communication module may include a transmitter and a receiver for receiving data from and transmitting data to the remote device, respectively.
  • the communication module may include a transceiver that combines the functions of a transmitter and a receiver.
  • the transmitter and receiver and the processing unit may communicate with each other. Communication may utilize any suitable means of communication, such as wired or wireless communication.
  • Images captured by the movable platform during motion may be transmitted from the movable platform or imaging device back to a control device or other suitable device for display, playback, storage, editing, or other purposes. Such transmission may occur in real-time or near real-time as the imaging device captures the imagery. Optionally, there may be a delay between the capture and transmission of the imagery.
  • the imagery may be stored in the removable platform's memory without being transferred anywhere else. The user can view these images in real time and, if necessary, adjust target information or other aspects of the movable platform or its components. Adjusted object information may be provided to the movable platform, and the iterative process may continue until the desired image is obtained.
  • the imagery may be transmitted to a remote server from the removable platform, the imaging device, and/or the control device. For example, images can be shared on some social networking platforms, such as WeChat Moments or Weibo.
  • the return-to-home starting point is the position of the movable platform when the return-to-home condition is triggered, and the return-to-home condition includes at least one of the following:
  • the work task of the movable platform is completed.
  • the movable platform obtains the return-to-home instruction sent by the control device.
  • the time when the movable platform is disconnected from the control device is greater than the preset time threshold.
  • the difference between the remaining power of the battery of the mobile platform and the power required for returning the mobile platform to home is less than or equal to a preset power threshold.
  • Another aspect of the present application also provides a path planning system for planning a moving path, wherein the system includes: a control device and a movable platform that are communicatively connected to each other, wherein: the control device and/or the movable platform include the above Path planning device.
  • the movable platform may specifically be an agricultural drone or an agricultural unmanned vehicle.
  • FIG. 22 is a schematic structural diagram of a movable platform provided by an embodiment of the present application.
  • the movable platform is an unmanned aerial vehicle 220
  • the unmanned aerial vehicle may include a plurality of power mechanisms 221 to drive the unmanned aerial vehicle 220 to fly.

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

一种路径规划方法、路径规划装置（2100）、路径规划系统和介质。方法用于规划可移动平台的移动路径，包括：获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的（S302）；至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径（S304）。

Description

路径规划方法、路径规划装置、路径规划系统和介质 技术领域
本申请涉及机器人技术领域，尤其涉及一种路径规划方法、路径规划装置、路径规划系统和介质。
背景技术
在机器人领域，很多典型的应用场景需要进行路径规划的操作。例如无人机、运输机器人等在封闭环境或开放环境内的路径规划。
然而，相关技术在进行路径规划时，无法满足用户个性化的路径规划需求，诸如在无人机返航的过程中，用户只能等待而无法干预无人机的返航过程，用户体验不好。
发明内容
有鉴于此，本申请实施例提供一种路径规划方法、路径规划装置、路径规划系统和介质，以便满足用户个性化的路径自动规划需求。
第一方面，本申请实施例提供了一种路径规划方法，用于规划可移动平台的移动路径，该方法包括：首先，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的；然后，至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径。
第二方面，本申请实施例提供了一种路径规划方法，用于规划可移动平台的移动路径，该方法包括：首先，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的；然后，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径。
第三方面，本申请实施例提供了一种路径规划装置，用于规划可移动平台的移动路径，该装置包括：一个或多个处理器；以及计算机可读存储介质，用于存储一个或多个计算机程序，计算机程序在被处理器执行时，实现：获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的；至少基于辅助点的位置信息规划可移动平台从 返航起始点移动到返航目标点的移动路径。
第四方面，本申请实施例提供了一种路径规划装置，用于规划可移动平台的移动路径，该装置包括：一个或多个处理器；以及计算机可读存储介质，用于存储一个或多个计算机程序，计算机程序在被处理器执行时，实现：获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的；若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径。
第五方面，本申请实施例提供了一种路径规划系统，用于规划移动路径，该系统包括：相互通信连接的控制装置和可移动平台，其中，控制装置和/或可移动平台包括如上的路径规划装置。
第四方面，本申请实施例提供了一种计算机可读存储介质，其存储有可执行指令，可执行指令在由一个或多个处理器执行时，可以使一个或多个处理器执行如上的方法。
本申请实施例中，通过引入辅助点，使得用户可以干预可移动平台的返航路径。如果被引入的辅助点的位置信息满足预设安全条件，则可以基于该辅助点生成安全性较高的移动路径，有助于提升可移动平台沿着该移动路径进行移动的安全性。
应当明白，本申请的不同方面可以被单独地、共同地或彼此结合地理解。本文所描述的本申请的各个方面可以适用于下文阐述的任何特定应用或者适用于任何其他类型的可移动平台。本文对诸如无人飞行器等飞行器的任何描述可适用于和用于多种可移动平台，诸如多种载具。另外，本文在空中运动(例如，飞行)的情景下公开的系统、设备和方法还可以适用于其他类型运动的情景下，诸如在地面上或在水上的移动、水下运动或者在太空中的运动。
本申请的附加方面的优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本申请的实践了解到。
附图说明
通过参照附图的以下详细描述，本申请实施例的上述和其他目的、特征和优点将变得更容易理解。在附图中，将以示例以及非限制性的方式对本申请的多个实施例进行说明，其中：
图1为本申请实施例提供的路径规划方法、路径规划装置、路径规划系统和介质的应用场景；
图2为本申请另一实施例提供的路径规划方法、路径规划装置、路径规划系统和介质的应用场景；
图3为本申请实施例提供的路径规划方法的流程示意图；
图4为本申请实施例提供的基于辅助点进行路径规划的示意图；
图5为本申请实施例提供的通过交互界面显示的地图设置辅助点的示意图；
图6为本申请实施例提供的语义地图的示意图；
图7为本申请实施例提供的更新语义地图的用户交互界面的示意图；
图8为本申请实施例提供的用户手动在语义地图上设置障碍物区域的示意图；
图9为本申请实施例提供的自动更新语义地图上障碍物区域的示意图；
图10为本申请实施例提供的基于语义地图和辅助点进行路径规划的示意图；
图11为本申请实施例提供的基于多个辅助点各自的获取时间排序进行路径规划的示意图；
图12为本申请另一实施例提供的基于多个辅助点的位置关系进行路径规划的示意图；
图13为本申请实施例提供的中间路径点的示意图；
图14为本申请实施例提供的安全距离的示意图；
图15为本申请另一实施例提供的安全距离的示意图；
图16为本申请实施例提供的杆量不满足安全条件时禁止响应打杆的示意图；
图17为本申请另一实施例提供的路径规划方法的流程示意图；
图18为本申请另一实施例提供的路径规划方法的流程示意图；
图19为本申请实施例提供的安全距离的示意图；
图20为本申请另一实施例提供的安全距离的示意图；
图21为本申请实施例提供的路径规划装置的结构示意图；以及
图22为本申请实施例提供的可移动平台的结构示意图。
具体实施方式
下面详细描述本申请的实施例，实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本申请，而不能理解为对本申请的限制。
为了便于理解本申请的技术方案，以下结合图1～图22进行示例性说明。
以无人机为例，返航路径规划是一种典型的应用场景。例如无人机飞出视野后的快速返航、运输机器人在复杂仓库环境内的返航运动等。返航的一大需求是在满足安全性的要求下，使得规划的移动路径尽可能的合理。
相关技术中，无人机(如消费级无人机)的返航路径是通过算法自动生成的，用户很难控制路径的中间状态。路径自动规划的好处虽然降低了用户实现路径规划的复杂度。但是，受限于当前规划算法的智能水平，自动规划的路径有时很难满足用户的特定需求。
本申请的实施例是基于辅助点的路径规划方式，其填补了返航目标点或目标路径点已被确定，机器人自动进行路径规划场景中，不能实现人工干预的技术空白。本申请实施例，还适用于在稳定环境下，用户可以便捷地干预自动规划的移动路径的中间路径状态。
图1为本申请实施例提供的路径规划方法、路径规划装置、路径规划系统和介质的应用场景。
以无人机返航场景为例进行示例性说明。当无人机完成作业、电量较低或存在被劫持风险等时，可以执行自动返航操作。如从返航起始点32(如无人机当前所在位置)返回至返航目标点31(如无人机上电的位置)。相关技术中，提供给规划算法的路径点信息只有起点和终点。本申请实施例中，除了起点和终点信息外，还提供了辅助点，起点、终点和辅助点这几个点共同描述了一个用户期望的航线。辅助点使得用户能够更多地参与到算法自动进行路径规划的过程中，如将用户对于移动路径的偏好引入到路径规划中。例如用户实际观察到某些区域的环境较为复杂，希望机器人能够避开这些复杂的场景。相关技术中在自动进行路径规划的过程中，受限于算法的智能性和环境信息的无法预知，机器人自动规划的移动路径可能会穿越那些实际的高 危险区域。
如图1所示，相关技术中基于返航起始点32和返航目标点31自动规划的移动路径可以如图1中返航起始点32和返航目标点31之间的虚线所示。无人机在按照自动规划的移动路径飞行的过程中，通过传感器检测环境信息，并执行自动避障，以实现基于规划好的移动路径安全地飞行至返航目标点31。然而，在这种场景中，规划好的移动路径并没有综合考虑用户需求或者额外的环境信息，使得该移动路径无法满足用户需求或并非较优的返航路径。例如，返航起始点32和返航目标点31之间的连线会经过不宜飞行的区域(如具有树林的区域、具有大面积湖泊的区域、具有大量电线的区域、具有大量飞鸟的区域等)，如果从这些不宜飞行的区域返航，则可能频繁触发诸如急刹车、减速、改变航向等操作，并且其对用于避障的传感器要求较高(如需要全向雷达等)，这会造成导致较高的安全风险和制造成本。又例如，用户希望无人机在返航的过程中路过指定的位置区域，以满足特定需求(如借助无人机进行拍摄，或者检测该指定的位置区域的温湿度、照度等需求)，相关技术无法满足上述需求。
此外，相关技术中可移动平台离不开复杂的传感器，如需要基于激光雷达、超声波雷达和图像传感器等实时建图以实现避障。但是复杂的传感器必然带来硬件成本的增加。此外，对于小型机器人(如小型无人机)而言，复杂的传感器会增加机器人的重量，并且挤占小型机器人内部用于设置能量存储介质、作业物品等的空间。以无人机植保场景为例，相关技术中是基于复杂的硬件传感器实时检测障碍物实现规划路径的，其一大应用基础就是每个机器人都配置了复杂的环境探测传感器。一方面，复杂的传感器必然带来硬件成本的提升。另一方面，对于环境信息较为固定，机器人携带的传感器有限的场景，当前的路径规划方案难以适应。
因此，对于比较稳定的运行场景，如果可以借助用户的知识或由外部提供针对该比较稳定环境的额外环境信息来辅助进行路径规划，能有效减少由于实时建图耗费的计算资源。例如，语义地图作为一种描述环境的方式，可以是一种配置文件，可以供多个机器人平台同时使用。由于机器人加载的地图相同，因此可以保证不同机器人在相同的条件下做出相同的规划结果。
需要说明的是，上述无人机返航场景仅为示例性说明，不能理解为对本 申请的限定。其中，无人机可以为消费级无人机、农业无人机以及行业应用无人机等。机器人可以是路上机器人、室内机器人、水上机器人、水中机器人、水底机器人、空中机器人等，在此不做限定。
本申请的实施例，通过引入辅助点的概念，使得用户能够通过控制辅助点的位置，大致描述其理想的返航路径，然后由算法根据辅助点信息，生成可执行的返航路径。本申请实施例提供了便于人工干预自动规划的移动路径的中间路径状态，并且可复用的路径规划方式。在稳定环境的场景中，还可以进一步借助用户的知识或由外部提供的针对该稳定环境的额外环境信息来优化移动路径，有效满足了用户的多种需求。
图2为本申请另一实施例提供的路径规划方法、路径规划装置、路径规划系统和介质的应用场景。如图2所示，以搭载在可移动平台10上的作业设备为例进行说明。
图2中可移动平台10包括本体11、承载体13及作业设备(如植保设备、测绘设备或图像捕捉装置等)。尽管可移动平台10被描述为飞行器，然而这样的描述并不是限制，前述描述的任何类型的可移动平台都适用。在某些实施例中，作业设备14可以直接位于可移动平台10上，而不需要承载体13。可移动平台10可以包括动力机构15，传感系统12。此外，该可移动平台10还可以包括通讯系统。
通讯系统能够实现可移动平台10与具有通讯系统的控制装置20通过天线22收发的无线信号30进行通讯，天线22设置在本体21上。通讯系统可以包括任何数量的用于无线通讯的发送器、接收器、及/或收发器。
在某些实施例中，控制装置20可以向可移动平台10、承载体13及作业设备中的一个或者多个提供控制指令，并且从可移动平台10、承载体13及作业设备中的一个或者多个中接收信息(如障碍物、辅助点的位置信息、地图信息、可移动平台10、承载体13或者作业设备的位置及/或运动信息，负载感测的数据，如液位信息、流量信息、温度信息等)。在某些实施例中，控制装置20的控制数据可以包括关于位置、运动、制动的指令，用于对可移动平台10、承载体13及/或作业设备的控制。例如，控制数据可以导致可移动平台10位置及/或方向的改变(如通过控制动力机构15)，或者导致承载体13相对于可移动平台10的运动(如通过对承载体13的控制)。控制装置20 的控制数据可以导致负载控制，如控制喷洒设备的操作(开启喷洒、停止喷洒、控制流量、喷洒角度、喷洒液体配比等)。在某些实施例中，可移动平台10、承载体13及/或作业设备的通讯可以包括一个或者多个传感器(如距离传感器12、距离传感器、水位传感器、角度传感器等)发出的信息。通讯可以包括从一个或者多个不同类型的传感器(如GPS传感器、运动传感器、惯性传感器、近程传感器或者影像传感器)传送的感应信息。控制装置20传送提供的控制数据可以用于控制可移动平台10、承载体13或者作业设备中一个或者多个的状态。可选地，承载体13及作业设备中一个或多个可以包括通讯模块，用于与控制装置20通讯，以便控制装置20可以单独地通讯或者控制可移动平台10、承载体13及作业设备。其中，控制装置20可以为可移动平台10的遥控器，也可以为诸如手机、iPad、可穿戴电子设备等能够用于控制可移动平台10的智能电子设备。
需要说明的是，控制装置20可以远离可移动平台10，以实现对可移动平台10的远程控制，可以固定或可拆卸地设于可移动平台10上，具体可以根据需要设置。
在某些实施例中，可移动平台10可以与除了控制装置20之外的其它远程设备，或者非控制装置20的远程设备通讯。控制装置20也可以与另外一个远程设备及可移动平台10进行通讯。例如，可移动平台10及/或控制装置20可以与另一个可移动平台或者另一个可移动平台的承载体或负载通讯。当有需要的时候，另外的远程设备可以是第二终端或者其它计算设备(如计算机、桌上型电脑、平板电脑、智能手机、或者其它移动设备)。该远程设备可以向可移动平台10传送数据(如传输语义地图)，从可移动平台10接收数据(如障碍物信息)，传送数据给控制装置20，及/或从控制装置20接收数据。可选地，该远程设备可以连接到因特网或者其它电信网络，以使从可移动平台10及/或控制装置20接收的数据上传到网站或者服务器上。
需要说明的是，可移动平台10还可以是陆地机器人、无人车、水下机器人等，在此不做限定。
图3为本申请实施例提供的路径规划方法的流程示意图。如图3所示，该路径规划方法，用于规划可移动平台的移动路径，可以包括操作S302～操作S304。
在操作S302，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的。
在本实施例中，可移动平台的运行环境可以指可移动平台在进行移动、作业等时所处的环境。该环境可以是开放式的，如在室外进行植保作业的环境、进行地质勘探的环境等。该环境可以是半封闭式的，如在具有厂房的场地中进行作业(如搬运、分拣等)。该环境可以是全封闭式的，如在封闭的超净间中进行作业等。
辅助点可以是一个虚拟的点，该辅助点对应于运行环境中一个具体的位置，如一个二维坐标或三维坐标等，使得可以准确地定位该运行环境中的具体位置。该辅助点可以是借助于地图等进行设定的，如在控制装置显示的地图上设置。该辅助点也可以是借助于实体设备进行设定的，如在具体位置放置了一个信号发射设备，使得可移动平台可以基于该信号发射设备确定辅助点的位置，以便途径该辅助点的位置(或该辅助点附近的位置)。
在一个实施例中，辅助点的位置信息可以由远程的控制装置基于用户操作确定的，如用户通过点击、坐标输入等方式确定辅助点的位置信息。例如，控制装置上设置有按键、拨杆等部件，用户可以通过操作这些部件输入辅助点的位置信息。又例如，控制装置上可以包括显示屏，用户可以通过显示屏上显示的交互组件(如虚拟的按键、摇杆等)来输入辅助点的位置信息。
进一步地，用户操作还可以是基于手势识别、姿势识别、体感或语音识别等方式确定并输入。例如，用户可以通过倾斜控制装置，以控制交互界面上光标的位置、移动方向、或者其它方面。控制装置的倾斜可以由一个或者多个惯性传感器所侦测，并产生对应的指令(如运动指令)。需要说明的是，用户还可以基于用户操作输入针对诸如语义地图、负载等的操作指令，如可以利用触控屏调整负载的操作参数(如喷洒参数、测绘参数等)、负载的姿态(通过承载体)，或者可移动平台上的任何物体的其它方面。
在一个实施例中，辅助点的位置信息可以是预先设置好的，通过调用文件等方式确定在本次任务中所使用的辅助点。例如，辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。这样不但便于用户设置辅助点，在需要借助地图等外界信息来定位辅助点时，还可以避免对地图等外界信息等的初始信息进行修改，提升了地图等外界信息等复用便捷度。
在操作S304，至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径。
在本实施例中，基于上述设置的辅助点的位置信息使得用户可以干预可移动平台从返航起始点移动到返航目标点的移动路径的中间路径的状态，能满足用户的多种特定需求，如个性定制化需求。
在一个实施例中，返航起始点的位置信息可以是在返航任务被触发时的位置信息，这样便于实现返航路径的自动规划。例如，返航起始点为返航条件触发时可移动平台的位置点，返航条件包括以下至少之一：可移动平台的作业任务(如植保、勘探、货运、分拣等)完成；可移动平台获取到控制装置发送的返航指令(如用户在应用APP界面上点击了返航按钮)；可移动平台与控制装置断开通信连接的时间大于预设时间阈值(如无人机信号中断、被信号干扰或存在较高的被劫持风险等)；可移动平台的电池的剩余电量与可移动平台返航所需电量之差小于或等于预设电量阈值。
参考图1，移动路径并非如图1中返航起始点32和返航目标点31之间的虚线所示，而是如图1中经过辅助点5的实线所示。通过设置该辅助点5，使得无人机可以绕过一些对飞行操作不友好的区域(如树林区域、大湖泊区域等)，提升无人机的返航安全性。此外，由于优化后的移动路径可能绕过了障碍物多的区域，使得有效减少了急刹车、改变飞行方向的情况发生的概率，有助于提升能量利用效率，并且有助于减少返航用时。此外，由于优化后的移动路径上障碍物较少，使得可以应用于避障能力较弱的入门级或针对稳定场景的可移动平台，降低了可移动平台的制造成本。
例如，为了便于规划移动路径，可以通过连接返航起始点32、辅助点5和返航目标点31来规划移动路径。需要说明的是，图1中辅助点的个数是1个，但是，可以根据用户需求设置多个辅助点。辅助点可以是在路径规划之前确定的，还可以是在按照移动路径进行移动的过程中确定，在此不做限定。
多个辅助点的连接方式可以基于用户选择的辅助点连接策略来确定，如按照辅助点生成的时间顺序进行排序的策略、按照辅助点距离可移动平台当前距离的顺序进行排序的策略、按照辅助点距离返航起始点或返航目标点的顺序进行排序的策略、按照规划的移动路径的总长度进行排序的策略等。
在一个实施例中，至少基于辅助点的位置信息规划可移动平台从返航起 始点移动到返航目标点的移动路径可以包括如下操作。
首先，连接返航起始点、辅助点和返航目标点，得到参考移动路径。然后，平滑参考移动路径得到移动路径，移动路径的平滑度满足可移动平台的机动要求。需要说明的是，当对参考移动路径进行平滑处理之后，平滑的移动路径可以经过该辅助点或不经过该辅助点。其中，当平滑的移动路径不经过该辅助点时，会经过该辅助点附近范围内，如以辅助点为圆心，预设偏移阈值为半径的圆形区域内。
图4为本申请实施例提供的基于辅助点进行路径规划的示意图。
如图4所示，规划好的移动路径是一条较平滑的路径，这样通过优化移动路径使得移动路径的平滑度满足可移动平台的机动要求，减少按照该移动路径进行移动所消耗的资源，如可以减少刹车、减速等操作的次数，降低能量、时间和计算量等的消耗。
本公开实施例提供的路径规划方法，通过引入辅助点，使得用户可以便捷地干预：自动规划得到的移动路径的中间路径状态，能满足用户针对移动路径规划的多种需求。
以下以基于针对控制装置的用户操作，来确定辅助点进行示例性说明。
在一个实施例中，辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，交互界面显示有可移动平台的运行环境的地图。
具体地，控制装置的交互界面上可以显示有地图，该地图中每个坐标(或像素)对应于可移动平台的运行环境的一个真实空间位置(或区域)。这样使得用户可以通过对地图的操作来确定该辅助点的位置信息。其中，该地图可以是自行构建的，也可以是从网上下载的，还可以是兴趣爱好者通过诸如航拍等方式获取的，在此不做限定。
图5为本申请实施例提供的通过交互界面显示的地图设置来辅助点的示意图。
如图5所示，以可移动平台是无人机，并且从外部导入地图为例进行说明。可以在地图上显示与返航起始点32和返航目标点31对应的点，其中，返航起始点32可以为无人机当前所在位置相对于地图的坐标。返航目标点31可以为无人机上电时所在位置相对于地图的坐标。用户通过点击地图的特定位置、或者调用文件等方式在地图上设置了辅助点5。依次连接返航起始 点32、辅助点5和返航目标点31，得到参考移动路径，然后对参考路径进行平滑处理使得该参考路径满足无人机机动要求，如满足转向半径要求、减少刹车、减速等操作等。平滑处理后的移动路径可以不经过该辅助点的位置，而是从辅助点的侧边通过。例如，在可移动平台趋近于与当前辅助点对应的区域的过程中，可移动平台的移动方向逐渐趋近于当前辅助点与下一辅助点之间连线方向。
在一个实施例中，地图包括语义地图，语义地图中各个图像区域的语义信息与可移动平台的避障策略具有对应关系。以下对语义地图进行示例性说明。
图6为本申请实施例提供的语义地图的示意图。
如图6所示，语义地图可以是一种像素图片(可以是tif/tfw格式)，图片中每个像素对应一个真实世界的坐标位置，同时该像素存储了一个表示与该位置对应的语义信息，标注了位置对应的物体类型。为了便于使用该语义地图，可以将多个具有相同语义且相邻的像素共同组成一个图像区域。每个图像区域具有对应的语义信息。其中，每个图像区域可以采用不同的颜色、填充图样等进行区别表示。例如，绿色像素点对应的都是农田的语义，表示这些像素点对应的实际位置是“农田”这种真实的物体。又例如，紫色像素点对应的都是“树木”这种物体。又例如，图6的语义地图中具有原点填充图样的图像区域的语义信息是麦田。具有纯白色填充图样的图像区域的语义信息是河流。具有横线填充图样的图像区域的语义信息是禁飞区。具有网格填充图样的图像区域的语义信息是建筑。具有斜线填充图样的图像区域的语义信息是玉米地。具有竖线填充图样的图像区域的语义信息是高压线塔。
需要说明的是，以上语义划分的颗粒度是可调整的。例如，可以根据需求将颗粒度调大，如可以将麦田和玉米地划分为同一类：农作物；将高压线塔合并在建筑中。当然，可以根据需求将颗粒度调小，如建筑可以划分为高层建筑、矮层建筑等。
语义地图的获取可以包含多种方式，不限定语义地图的来源。例如，语义地图可来自于航拍建图识别、用户手动划定、第三方下载等。
语义地图可以包括多个图像区域，每个图像区域中各自的像素对应的避障策略相同。例如，麦田区域中各像素对应的语义信息都是麦田，麦田区域 对应的避障策略是通行。可以分别为每个像素设置对应的语义信息，也可以仅为每个图像区域设置对应的语义信息，在此不做限定。
语义地图中图像区域的语义信息与可移动平台的避障策略的对应关系，可以是由用户设置的，也可以是由厂商设置的，还可以是由绘制该语义地图的用户设置的，在此不做限定。上述对应关系可以由用户进行修改，如修改语义地图中图像区域、修改图像区域的语义信息、修改与语义信息对应的避障策略等。
可以将语义地图和辅助点作为路径规划的输入，基于语义地图中各图像区域的语义信息确定与参考移动路径对应图像区域的避障策略，进而基于避障策略进行路径规划。参考图6的语义地图中，针对原点填充图样和纯白色填充图样的图像区域的避障策略是通行，针对横线填充图样和网格填充图样的图像区域的避障策略是绕行，针对斜线填充图样的图像区域的避障策略是上方通过。这样就可以便捷地对稳定环境下可移动平台的移动路径进行规划，而不仅仅依靠可移动平台自身携带的传感器进行路径规划，并且由于语义地图给出的环境信息可靠度较高，有助于提升规划的路径的可靠性。
需要说明的是，上述避障策略仅为示例，避障策略可以具有更多或更少的策略。例如，避障策略仅包括：通行和绕行。又例如，避障策略包括通行、绕行、上方通过、下方通过、快速通过、低速通过等，在此不做限定。
本申请实施例提供的路径规划方法，借助于辅助点以及语义地图中各个图像区域的语义信息与可移动平台的避障策略之间具有对应关系，使得可移动平台可以基于辅助点和参考移动路径经由的图像区域对应的避障策略进行路径规划，可以在复杂场景中实现更为合理、高效的路径规划。
需要说明的是，语义地图中包括的环境信息可编辑，使得用户可根据实际场景编辑环境信息。与相关技术中的机器人实时监测环境不同，语义地图是可以预先修改，根据实际情况配置的，提高了其应用的灵活性。
在一个实施例中，至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径可以包括如下操作。
首先，根据辅助点、返航起始点、返航目标点在语义地图中对应的位置信息，确定目标图像区域。
然后，至少基于辅助点的位置信息以及目标图像区域的语义信息对应的 可移动平台的避障策略，规划可移动平台从返航起始点移动到返航目标点的移动路径。
以下对确定目标图像区域、返航起始点和返航目标点等进行示例性说明。
在本实施例中，语义地图可以是由用户输入至可移动平台或该可移动平台的控制装置的。语义地图也可以是可移动平台或该可移动平台的控制装置自动下载的，如基于可移动平台当前的位置信息从语义地图集合中搜索得到的。语义地图也可以是存储在可移动平台或该可移动平台的控制装置的本地中，在可移动平台上电后自动从存储空间中读取的。语义地图可以是由其它电子设备绘制的，也可以是由自身预先绘制的。
例如，避障策略包括：侧面绕行策略、上方通过策略或下方通过策略中至少一种。
参考图6所示，该语义地图中包括六个图像区域，其中，各图像区域的语义信息分别为：麦田、水面、建筑、禁飞区、玉米地和高压线塔。各图像区域对应的避障策略可以为：通行、高速通行、绕行、禁止飞行、上方通过等。
在确定了目标图像区域之后，就可以基于上述对应关系从语义地图中确定与该目标图像区域对应的避障策略，以便基于该避障策略进行路径规划。
在一个实施例中，可以根据可移动平台的返航初始点、返航目标点和辅助点，在语义地图中对应的位置信息以及语义地图，确定目标图像区域。然后，根据目标图像区域，确定目标图像区域的语义信息。其中，返航初始点和返航目标点可以是由用户设定的，如用户设定可移动平台由位置A移动至位置B，则位置A是返航初始点，位置B是返航目标点。
返航初始点和返航目标点可以是由可移动平台自动确定的，如用户通过控制装置给可移动平台发送了返航指令、结束作业指定，或者可移动平台检测到了被劫持风险、接收到来自空管的返航指令、已完成预设作业任务时，以可移动平台的当前位置为返航初始点，以可移动平台的起始移动路径点为返航目标点。以可移动平台是无人机为例，移动路径的起点是返航起始点，终点是返航目标点。
例如，可以通过文件加载等方式在语义地图上标注与辅助点、返航起始点和返航目标点对应的标记，该标记包括但不限于：三角形、原点、圆圈、 十字线、瞄准标记等。该辅助点、返航起始点和返航目标点可以通过用户操作设置的，如用户点击了语义地图上的多个位置，如用户输入的一个或多个坐标。该返航起始点和返航目标点可以是由可移动平台自动设置的，如开始返航时的起点坐标作为返航起始点、可移动平台开始作业时的起点坐标作为返航目标点。可以在语义地图上显示返航初始点和返航目标点。
具体地，可以通过连接返航初始点和返航目标点来确定连线经过了哪些图像区域，或者通过连接返航初始点和辅助点、辅助点和返航目标点来确定连线经过了哪些图像区域，将这些图像区域作为目标图像区域。需要说明的是，对于目标图像区域对应的避障策略是绕行时，则需要将该目标图像区域相邻的至少一个图像区域增加到目标图像区域中，以便形成连续的移动路径。
例如，可以基于目标图像区域的语义信息和目标图像区域的轮廓来规划移动路径。例如，对于存在返航初始点和返航目标点的场景中，可以确定返航初始点和返航目标点之间的连线，如果连线与语义信息是绕行的目标图像区域相交，则可以基于该目标图像区域的轮廓生成替代移动路径(或多个路径点)以代替连线中与该目标图像区域相交的线段(或多个路径点)。其中，替代移动路径可以与该目标图像区域的至少部分轮廓共形或不共形。替代移动路径与该目标图像区域的轮廓之间需要设置安全距离。
其中，提取该图像区域的轮廓可以是在进行路径规划之前就完成的，也可以是在进行路径规划的过程中完成的，在此不做限定。
此外，在初步确定了移动路径之后，还可以进一步对该移动路径进行优化，例如，可移动平台在沿着该移动路径进行移动的过程中，尽量多的满足以下条件：尽量减少触发诸如急停、刹车等操作指令、尽量缩短路径长度、尽量降低能量消耗、尽量提升可移动平台的移动安全性等。
例如，移动路径满足以下至少一种条件：移动路径上的路径点与目标对象之间的距离大于安全距离；可移动平台从移动路径的返航初始点移动至返航目标点的资源消耗最优，资源包括以下至少一种：路径长度、能量或时间；移动路径的平滑度满足可移动平台的机动要求。其中，安全距离可以与可移动平台的尺寸、可移动平台的作业半径等相关，以保证可移动平台的飞行安全和作业效果。
需要说明的是，语义地图可以被进行更新。例如，为了提升基于语义地 图进行路径规划的适用性，用户可以基于自身需求对语义地图进行更新，使得更新后的语义地图更符合用户的需求或与可移动平台当前所处环境的适配度。
在一个实施例中，在获取可移动平台运行环境的语义地图之前，上述方法还可以包括如下操作。
首先，获取可移动平台运行环境的初始语义地图。然后，获取基于用户操作生成的语义地图更新信息。接着，根据语义地图更新信息更新初始语义地图，以得到可移动平台运行环境的语义地图。
其中，初始语义地图可以是从存储空间中读取出的语义地图，或者从网络中获取的语义地图，或者由用户输入的语义地图。该初始语义地图可以在交互界面中进行显示，以便用进行编辑。
图7为本申请实施例提供的更新语义地图的用户交互界面的示意图。
如图7所示，用户操作所针对的对象可以是与可移动平台通信连接的控制装置。用户在控制装置上输入以下至少一种信息：选取信息、点坐标输入信息、指定操作(如编辑、删除、新增)、对象以及该指定操作的参数值(如坐标值、安全距离、语义信息、避障策略)等。其中，控制装置可以是一体式的，如遥控器上设置有处理器、存储器、显示屏等。控制装置可以是分体式的，如遥控器可以和其它电子设备共同构成控制装置，如遥控器和智能手机互连后共同构成控制装置。其中，智能手机上可以安装有应用(APP)，该APP上可以输入操作指令、设置操作参数等。
具体地，可以获取基于用户在用户交互界面上的操作生成的语义地图更新信息。这样便于用户输入语义地图更新信息，以对语义地图进行编辑。
图7中的用户交互界面中可以包括编辑区域和效果展示区域。编辑区域中可以由用户输入语义地图更新信息。
在一个实施例中，语义地图更新信息包括语义地图中更新的图像区域的位置、形状和语义信息。其中，部分语义信息可以没有避障策略，如针对建筑的避障策略是绕行，该对应关系可以是全局通用的，如果用户在语义地图上新增了表征建筑的图像区域，则无需单独为该表征建筑的图像区域设置避障策略，而是基于已有的对应关系自动将其避障策略设置为绕行。此外，对于已有的图像区域的位置、形状和语义信息，其中至少部分信息可以进行由 用户进行编辑的，这样有效提升用户操作便捷度，也能更好地适用于更多的场景中。
参考图7所示，用户可以在编辑区域中对各部分信息进行更新，如新增一个对应关系，编辑对应关系或删除对应关系等。在编辑对应关系时，可以修改图案(如修改颜色、填充图案等)，可以修改语义信息(如将麦田修改为果园)，可以修改避障策略(如将通行修改为绕行或上方通过等)。
在一个实施例中，语义地图更新信息存储在配置文件中，使用的时候可以进行调取。这样不会直接修改原语义地图，便于重复使用该语义地图。
在一个实施例中，语义地图更新信息还包括语义地图中更新的图像区域的语义信息对应的避障策略。
具体地，可以由用户输入语义地图更新信息以设置更新的图像区域的语义信息对应的避障策略。例如，可以进一步设置避障策略，如在与地图中新添加了语义信息：礁石，礁石原本没有对应的避障策略，则需要提示用户进行设置，或者原本也有对应的避障策略，但是开放给用户进行修改。
当然，本申请实施例也可以修改语义地图中已有的图像区域的语义信息对应的避障策略。例如，语义地图更新信息包括初始语义地图中的图像区域的语义信息对应的避障策略。
图8为本申请实施例提供的用户手动在语义地图上设置障碍物区域的示意图。
如图8所示，用户可以根据需求直接在语义地图中设置障碍物区域，该障碍物区域用于表征虚拟的障碍物的，使得规划的移动路径绕过该障碍物区域。这样有效增加了用调整诸如作业区域的便捷度。例如，一片区域已经人工进行过药液喷洒，无需重复作业。又例如，一片区域近期可能施工或拉网，此时，用户可以通过用户交互界面在语义地图中对应的位置设置障碍物区域，使得规划的路径绕过该障碍物区域，有效提升了操作的灵活度。
以下对侧面绕行策略进行示例性说明。
侧面绕行策略可以是针对不适于从该图像区域对应的地理位置通行时采用的避障策略，降低可移动平台发生干涉的概率，并减小可移动平台在按照移动路径进行移动过程中，发生移动方向改变、急停、刹车等非期望的操作的概率，有助于提升移动效率，并有助于降低能耗。
在一个实施例中，侧面绕行策略包括：当目标对象的尺寸满足预设条件时，采用第一侧面绕行策略进行侧面绕行，当目标对象的尺寸不满足预设条件时，采用第二侧面绕行策略进行侧面绕行。例如，当目标图像区域中目标对象的尺寸过大，并且采用的类似弓字型移动路径时，如果采取侧面绕过障碍物，然后继续作业的策略，则会导致过多的移动路径是用于绕障碍物的，会降低作业效率。又例如，当目标图像区域中的目标对象的尺寸较小，可以很快地绕过该障碍物，则可以采取绕过障碍物的作业策略。
具体地，可以通过比较目标对象的尺寸和可移动平台的作业路径间距确定目标对象的尺寸是否满足预设条件。其中，目标对象的尺寸可以指目标对象的最大尺寸，如最大宽度、最大长度或最大高度等。
例如，第一侧面绕行策略包括：移动至相邻的作业路径。第二侧面绕行策略包括：从侧边绕行以继续当前的作业路径。
为了便于理解语义信息与避障策略之间的对应关系，表1中示例性列出了可移动平台是无人机场景中一些语义值与避障策略之间的对应关系。
表1
Figure PCTCN2020127634-appb-000001
Figure PCTCN2020127634-appb-000002
表1中还示出了高度信息的概念，以下对高度信息进行示例性说明。参考图1所示，标号1115所示的图形区域对应的语义信息是玉米地，玉米地的高度虽然比麦田的高度高，但是，对于无人机而言，可以通过上方通过的方式进行移动，无需从侧面绕行，有助于减小移动路径的长度。
在一个实施例中，上述方法还可以包括如下操作，获取目标图像区域对应的高程信息。
例如，高程信息可以是从具有高程信息的语义地图中读取的。该具有高程信息的语义地图可以是通过融合高程地图和语义地图得到的。又例如，该具有高程信息的语义地图可以是由用户自行标注高程信息后生成的。又例如，该具有高程信息的语义地图可以是由具有图像传感器和测距传感器的测绘设备直接生成的。高程信息可以是一个具体的高度值，也可以是一个高度范围等。
在一个实施例中，可以根据目标图像区域的语义信息对应的可移动平台的避障策略以及目标图像区域对应的高程信息，规划可移动平台避开目标图像区域对应的目标对象的移动路径。具体地，当避障策略包括上方通过时，根据目标图像区域的语义信息对应的可移动平台的避障策略以及目标图像区域对应的高程信息，规划可移动平台避开目标图像区域对应的目标对象的移动路径。
需要说明的是，该高程信息的高度值是相对于地面而言的，也可以是相 对于水平面而言的，在此不做限定。对于环境信息较为固定的场景中而言，该高程信息的高度值可以是相对于预设的一个平面的，如地平面的高度值。
在一个实施例中，上述方法还包括：基于可移动平台检测到的障碍物更新语义地图。例如，如果确定语义地图中某个图像区域存在的障碍物信息满足一定条件，则可以确定该障碍物是较稳定的障碍物，可以针对该障碍物信息对语义地图进行更新。
图9为本申请实施例提供的自动更新语义地图上障碍物区域的示意图。
以可移动平台是无人机为例进行说明，如果无人机在多次作业的过程中，在禁飞区附件的同一位置范围内检测到障碍物的次数(比例)满足预设条件，则可以确定该障碍物会较稳定的处于该区域。因此，如图9所示，可以在语义地图上对应的位置处设置一个障碍物区域。
在本实施例中，可移动平台在按照规划好的移动路径进行移动的过程中，也可以基于检测到的障碍物信息更新语义地图。其中，可以是直接修改的初始语义地图，也可以是以配置文件的方式新增针对该语义地图的障碍物区域。在一个实施例中，还可以基于该障碍物的稳定度确定是否基于配置文件中的障碍物区域更新初始语义地图。例如，植保无人机在针对指定区域的作业过程中或返航过程中，连续多次在同一位置检测到障碍物信息，或者，在持续超过预设时间阈值(如1周、1个月、1年)在同一位置检测到障碍物信息，则可以将配置文件中稳定存在的障碍物区域固化在初始语义地图中。这样可以实现初始语义地图的自动更新。
需要说明的是，障碍物区域可以是可移动平台基于预设规则自动对语义地图进行更新的，还可以是由用户自行设定的。例如，用户在进行一次作业之前，可以将在语义地图上无需作业或需要规避的区域(如可能存在障碍物的图像区域)设置障碍物区域，以满足用户的多样化需求。
图10为本申请实施例提供的基于语义地图和辅助点进行路径规划的示意图。
如图10所示，语义地图1中具有原点填充图样1111的图像区域的语义信息是麦田。具有纯白色填充图样1112的图像区域的语义信息是河流。具有横线填充图样1113的图像区域的语义信息是禁飞区。具有网格填充图样1114的图像区域的语义信息是建筑。具有斜线填充图样1115的图像区域的语义信 息是玉米地。具有竖线填充图样1116的图像区域的语义信息是高压线塔。
规划出来的移动路径并不是返航起始点32和返航目标点31之间的直线，也不是返航起始点32和辅助点51、52之间的直线以及返航目标点31与辅助点51、52之间的直线，而是如位于返航起始点32和返航目标点31之间的虚线所示。无人机2可以按照规划好的移动路径从与返航起始点31对应的位置移动至与返航目标点32对应的位置。其中，移动路径绕过了横线填充图样1113的图像区域，该区域对应的避障策略是绕行策略。移动路径穿过了纯白色填充图样1112的图像区域，该区域对应的避障策略是通行。移动路径从辅助点52附近通过，以满足用户的特定需求。移动路径上方通行经过斜线填充图样1115的图像区域，该区域对应的避障策略是上方通行。移动路径没有经过辅助点51附近，因辅助点51所在的区域是竖线填充图样1116的图像区域，该区域对应的避障策略是绕行，以提升无人机2的飞行安全性。此外移动路径经过了平滑处理，使得无人机2沿着移动路径移动时能以尽量少的减速等指令下进行移动，满足机动要求。
关于移动路径没有经过辅助点51附近会在后续部分进行说明。
在一个实施例中，辅助点的数量为多个。
相应地，上述方法还可以包括：对多个辅助点进行排序。例如，可以基于辅助点连接策略来对辅助点进行排序，不同的辅助点连接策略对应不同的排序算法。具体地，可以针对一个指标或多个指标对辅助点进行排序。指标包括但不限于：辅助点生成时间、辅助点相对于指定点之间的距离、按照排序规划的移动路径的长度、按照排序规划的移动路径的移动用时、按照排序规划的移动路径的能量消耗等。
相应地，连接返航起始点、辅助点和返航目标点，得到参考移动路径可以包括如下操作：按照排序依序连接返航起始点、多个辅助点和返航目标点，得到参考移动路径。
在一个实施例中，对多个辅助点进行排序可以包括：按照获取多个辅助点的时间顺序对辅助点进行排序。
图11为本申请实施例提供的基于多个辅助点各自的获取时间排序进行路径规划的示意图。
如图11所示，辅助点52的获取时间早于辅助点51的获取时间，因此， 返航起始点32与辅助点52之间进行相连，辅助点52和辅助点51之间进行相连，辅助点51和返航目标点31之间进行相连。需要说明的是，图11中仅示出了两个辅助点，还可具有更多个或更少各辅助点，在此不做限定。图11中移动路径没有经过平滑处理，为了满足诸如无人机飞行机动要求，可以对该移动路径进行平滑处理。此外，难免用户会出现手误或希望取消之前设定的辅助点的情形，用户可以通过在诸如APP显示界面上通过诸如“撤销”、“删除”等按钮对已设定的辅助点进行操作。
例如，可以按照排序依序连接多个辅助点和目标点，得到多个依序连接的子参考移动路径，然后，基于多个依序连接的子参考移动路径规划可移动平台的移动路径。
在一个实施例中，对多个辅助点进行排序可以包括：按照多个辅助点和返航起始点或返航目标点的相对位置关系对多个辅助点进行排序。
图12为本申请另一实施例提供的基于多个辅助点的位置关系进行路径规划的示意图。
如图12所示，辅助点52相对于返航起始点32之间的距离，大于辅助点51相对于返航起始点32之间的距离，因此，返航起始点32与辅助点51之间进行相连，辅助点52和辅助点51之间进行相连，辅助点52和返航目标点31之间进行相连。同上，图11中仅示出了两个辅助点，还可具有更多个或更少各辅助点，在此不做限定。图11中移动路径同样可以进行平滑处理。通过以上方式有助于降低移动路径的长度。
在一个实施例中，为了便于用户临时改变移动路径的需求，如在可移动平台按照规划好的移动路径进行移动的过程中，同样可以设置或更新辅助点。
具体地，可以先获取临时辅助点，然后，基于辅助点、临时辅助点和目标点更新可移动平台的移动路径。
例如，在可移动平台按照移动路径进行移动的过程中，获取临时辅助点，将临时辅助点作为多个辅助点中相对于当前辅助点的下一个辅助点。例如，将临时辅助点作为多个辅助点中与临时辅助点最接近的两个辅助点之间的辅助点，以确定多个辅助点和临时辅助点各自的先后顺序。例如，将临时辅助点作为最后路过的辅助点的下一个辅助点，以确定多个辅助点和临时辅助点各自的排序。这样使得可以至少基于多个辅助点和临时辅助点各自的先后顺 序更新可移动平台的移动路径。
在一个实施例中，可以根据辅助点的位置先确定目标图像区域，在目标图像区域中找到移动路径的中间点，以便基于中间点进行路径规划。相应地，至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径可以包括如下操作。
首先，至少基于辅助点的位置信息在可移动平台的运行环境中确定移动路径所在的目标三维区域。
然后，在目标三维区域中确定中间路径点，以规划可移动平台从返航起始点途径中间路径点移动到返航目标点的移动路径。例如，可以通过优化目标损失函数的方式在目标三维区域中确定中间路径点。
具体的，可以连接返航起始点、辅助点和返航目标点，并基于该连线确定目标三维区域。例如，将该连线作为中轴线形成管道型的目标三维区域。
具体地，在目标三维区域中确定中间路径点可以包括如下操作，优化目标损失函数以确定中间路径点的运动参数，中间路径点的运动参数至少包括位置参数。可选的，还可以包括速度参数、加速度参数等。
其中，优化目标损失函数以确定可移动平台避开目标对象的移动路径可以包括：最小化目标损失函数以确定多个目标轨迹点对应的可移动平台的位置参数，多个目标轨迹点对应的可移动平台的位置参数使得目标损失函数的函数值最小。目标损失函数可以包括以下至少一种：碰撞代价函数，用于约束移动路径上的路径点和障碍物之间的距离。另外，该目标损失函数还可以包含辅助点代价函数，用于约束移动路径上的路径点和辅助点之间的距离。进一步的，该目标损失函数还可以包含路径长度代价函数，用于约束移动路径的总长度。此外，该目标损失函数还可以包含运动学和动力学代价函数，保证得到的移动路径为可移动平台可执行的移动路径。以上所示的代价函数仅为示例性示出，不能理解为对本申请的限定。例如，对于多种可以影响到路径规划的参数都可以设置对应的代价函数。
图13为本申请实施例提供的中间路径点的示意图。
如图13所示，目标三维区域中确定了多个中间路径点，这样就可以连接多个中间路径点来生成针对该目标三维区域的移动路径。
在一个实施例中，至少基于辅助点的位置信息规划可移动平台从返航起 始点移动到返航目标点的移动路径可以包括：若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径。
在本实施例中，辅助点满足预设安全条件时，有助于提升可移动平台按照移动路径进行移动时的安全性，如该辅助点不会使得可移动平台与障碍物或障碍物区域发生干涉。
例如，用户交互界面显示语义地图，预设安全条件包括但不限于以下至少一种：辅助点没有设置在禁止通过(如禁飞、空中管制、交通管制等)区域中、辅助点没有设置在语义地图中障碍物区域中、辅助点没有设置在语义地图中避障策略是绕行策略的区域中等。
在一个实施例中，上述方法还可以包括如下操作，若辅助点的位置信息不满足预设安全条件，则更新辅助点的位置信息，以至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径。
具体地，可以通过修改辅助点的位置信息，使得修改后的辅助点的位置信息满足预设安全条件。
例如，可以连接辅助点和距离辅助点最近的障碍物的轮廓点，将连线延伸至障碍物安全半径以外，以更新辅助点的位置信息。
例如，更新后的辅助点是针对预设指标的最优辅助点，并且满足安全条件，预设指标包括以下至少一种：距离、能量消耗或者路径长度。又例如，为了便捷地更新辅助点的位置信息，可以将与待更新的辅助点最近的两个点(可以是辅助点、返航起始点、返航目标点等中的两个点)相连以得到连线，然后经由待更新的辅助点做上述连线的垂线，从垂线上选取距离待更新辅助点最近且满足安全距离的位置来更新辅助点的位置信息。
在一个实施例中，上述方法还可以包括如下操作，若辅助点的位置信息不满足预设安全条件，则删除辅助点的位置信息。这样可以简单有效地降低可移动平台按照移动路径进行移动过程中的风险。
参考图10所示，标号为1116的图像区域表征高压线塔，对应的避障策略是绕行策略，而辅助点51设置在了该区域中，为了降低无人机的飞行安全风险，可以直接删除或忽略该辅助点51，同时，为了便于用户了解规划的移动路径没有经过辅助点51(或附近)的原因，可以在交互界面中展示提示信 息，如辅助点51设置在了危险区域，已删除辅助点51。
在一个实施例中，预设安全条件可以包括：辅助点与距离辅助点最近的障碍物的距离大于预设安全距离阈值。其中，障碍物可以是实体的障碍物，也可以是虚拟障碍物，例如用户选定的需要绕行的障碍物区域或者电子围栏区域等。
如表1中还示出了安全距离的概念，以下对安全距离进行示例性说明。
在一个实施例中，避障策略还包括安全距离信息，安全距离信息可以是用于指示可移动平台相对于目标图像区域对应的目标对象的最小间距。
如表1中所示，具有不同语义信息的图像区域各自可以具有不同的安全距离，以在保证移动安全性的基础上减少移动路径的长度。例如，相对于树木而言，在建筑物周围遇到需要可移动平台进行减速、急刹车等非期望操作的概率更高，如可能由于行人、人为设置的物体等导致该情形。因此，可以为语义地图中表征建筑物的图像区域设置更大的安全距离，如增大与语义值对应的安全距离的取值。又例如，相对于普通建筑物而言，电线产生的电磁辐射可能对控制装置与可移动平台之间的通讯造成较大的干扰，因此，可以为语义地图中表征电线的图像区域设置更大的安全距离。
具体地，安全距离与以下至少一种相关：可移动平台的尺寸、可移动平台的作业半径。例如，避障策略包含安全距离信息，避障策略和语义信息有关，这样就可以便捷地确定安全距离信息和语义信息之间的对应关系。此外，由于不同的可移动设备各自具有不同的最小避障距离，如高速行驶下的路面机器人的刹停距离大于低速行驶下的路面机器人的刹停距离，相同行驶速度下，空中机器人的刹停距离大于路面机器人的刹停距离等。因此，可以分别基于可移动平台的最小避障距离设置安全距离，以提升可移动平台的安全性。
图14为本申请实施例提供的安全距离的示意图。图15为本申请另一实施例提供的安全距离的示意图。
如图14、图15所示，该安全距离可以是针对两种场景下的距离，参考图中的双向箭头线段所示。例如，图14中所示的安全距离，是针对语义地图中避障策略是绕行的图形区域，在可移动平台绕行某个图形区域对应的区域时，可移动平台与该区域之间的距离需要大于安全距离。图15中所示的安全距离，是针对可移动平台按照规划好的移动路径进行移动过程中，针对检测 到的障碍物，需要控制可移动平台与该障碍物之间的距离大于安全距离。
在一个实施例中，可移动平台可以基于规划好移动路径进行移动。在移动过程中，需要基于实时检测到的障碍物信息进行避障。但是，相对于不采用辅助点和/或语义地图进行路径规划的场景中，本实施例采取的传感器的复杂度可以大幅度降低。例如，相关技术在进行自动返航过程中，为了保证可移动平台的移动安全，可以采用诸如全向雷达以及诸如图像传感器等，而本申请的技术方案可以只采用双向雷达即可，在降低硬件成本的同时，也降低了机身重量、计算资源消耗和能源消耗等。
具体地，在根据目标图像区域的语义信息对应的可移动平台的避障策略，规划可移动平台避开目标图像区域对应的目标对象的移动路径之后，上述方法还可以包括如下操作：控制可移动平台基于移动路径和可移动平台通过传感器检测到的障碍物信息进行移动。其中，可移动平台通过传感器检测到障碍物信息可以采用相关技术中检测障碍物的方法，如基于图像、雷达(如激光雷达或超声波雷达等)、测距传感器等进行检测，在此不做限定。
在一个实施例中，控制可移动平台基于移动路径和可移动平台通过传感器检测到的障碍物信息进行移动，可以包括：在传感器检测到的障碍物的置信度大于预设阈值时，控制可移动平台基于移动路径和可移动平台通过传感器检测到的障碍物信息进行移动，障碍物的置信度与重复检测到障碍物的次数以及检测到障碍物时的环境信息相关。
其中，如果障碍物的置信度小于一定阈值，则确定该障碍物的信息是不可靠的，可以忽略。如风雨天气下，可能会检测到树叶、雨滴等障碍物信息，但是这些障碍物的置信度较低，如在相邻的多个检测周期中检测的结果差别较大，则可以忽略该障碍物信息。例如，无人机在多次在同一位置检测到障碍物或无人机在一个较小的区域内连续检测到障碍物，则该障碍物信息的置信度较高。
在一个实施例中，还可以基于辅助点和/或语义地图实现类似地理围栏的效果，便于给可移动平台操控者设置操作规范，降低可移动平台移动至禁行区的风险。
例如，在根据辅助点、目标图像区域的语义信息对应的可移动平台的避障策略，规划可移动平台的移动路径之后，接收基于用户操作生成的控制杆 量。如果确定控制杆量会使得可移动平台进入与目标图像区域(如避障策略是绕行策略对应的图形区域)和/或远离相对于移动路径的下一个辅助点，则不响应控制杆量。例如，在无人机飞行比赛中，可以通过语义地图设置封闭的禁飞区，或者位于禁飞区之外的辅助点，或者在比赛场地中针对特定区域设置禁飞区，避免无人机操作不当对观众等造成伤害或参赛选手通过违规的方式进行比赛等。
图16为本申请实施例提供的打杆量不满足安全条件时禁止响应打杆的示意图。
如图16所示，虚线为可移动平台的移动轨迹，外围网格区域被设置为语义信息是建筑物，内部还设置有禁飞区。例如，如果用户的控制杆量会使得可移动平台会进入与建筑物对应的图形区域或与禁飞区对应的图形区域，则可移动平台会根据语义地图确定不响应该控制杆量。例如，如果用户的控制杆量会使得可移动平台远离距离可移动平台的当前位置最近的辅助点时，则可移动平台会根据语义地图确定不响应该控制杆量，这样可以基于辅助点对无人机操作进行引导，尤其适用于如图16所示的高风险区域，通过设置多个辅助点以提升引导效果。
图17为本申请另一实施例提供的路径规划方法的流程示意图
如图17所示，以可移动平台是无人机为例进行说明，路径规划的流程可以主要包括3个部分：输入条件准备、算法规划、执行。下面依次介绍各阶段的具体内容。
一、输入条件
输入条件是操作人员预先为返航任务设定的一些参数。
首先，设定起点和终点。
返航任务是从当前机器人所在的位置，安全的返回目标点，因此需要预先设定返航的起点和终点。默认情况下，返航的起点既是机器人当前位置，返航的终点可通过默认的原点(home点)或者用户通过app点击设定、或者通过配置文件的形式输入，本申请的技术方案不做限定。
然后，设定辅助点的位置。
其中，辅助点位置设定可以如如下两种方式所示。例如，用户在交互界 面上依次点击各辅助点，并调整其位置。又例如，用户修改像配置文件的形式设定辅助点。
接着，设定绕行障碍物信息(该操作是可选操作)。
对于已知的障碍物，用户可以通过该操作预先设定需要绕行的区域，也可以由机器人实时探测获得。
然后，设定规划参数。
其中，规划参数包括但不限于：机器人距离障碍物的最小安全距离、机器人运动限制参数、机器人飞行高度等。
二、算法规划
首先，规划地图生成。
规划地图是算法内部的一种存储结构，保存了用户规划算法计算的数据。例如，可以将一些已知的环境信息加载到算法中，同时，对于实时规划的场景，障碍物也可以由机器人的传感器探测，然后将障碍物信息加载到规划地图中，然后规划生成路径。
然后，检查语义点安全性，生成规划段序列。
辅助点可以是定义了规划路径的大致形状，一般生成的航线都会经过辅助点附近。由于其由用户设定，所以难免与实际的障碍物信息重合，即辅助点在障碍物安全半径以内，如果将这些辅助点引入到规划中，最终生成的航线势必会出现较大的危险性。因此，需要对不安全的辅助点进行过滤，如可以采用如下两种处理方式：例如，直接将不安全的辅助点删除。例如，在不安全的辅助点周围寻找一个替代的辅助点。
接着，对各段运行规划算法，并将各段路径依序连接。
例如，用户共依次点击了{0，1，2，3，4}五个点，其中0＝起点，4＝终点，{1，2，3}为辅助点，由于3号辅助点在语义地图中与语音“建筑物”对应的图形区域内，因此删除辅助点(3)。经过过滤后，共存在在{0，1，2，4}四个航线规划的参考点，共3段航线规划段：[0,1][1,2][2,4]。对上述三段分别进行路径规划，获得三段航线，然后将三段航线依次连接，形成最终的返航航线。进一步地，可以对三段航线进行平滑处理。
然后，输出返航路径。
在规划算法执行结束后，还需要对路径做适当的格式处理(如将移动路径处理成可移动平台能读取的数据格式)，使其满足后期执行的要求，然后输出路径。
三、飞行控制执行路径
无人机的执行机构获取移动路径，并执行该移动路径。
至此，借助辅助点规划移动路径的规划过程结束。参考图10所示，可以观察到，规划路径结果大致按照辅助点52定义的方向运动。
以下以无人机及其控制装置为例，对上述各操作的执行主体进行示例性说明。其中，无人机及其控制装置之间可以相互传输以下涉及的至少部分信息。
可以由无人机和/或其控制装置获取辅助点的位置信息。
可以由无人机和/或其控制装置确定是否触发返航条件。
可以由无人机和/或其控制装置获取可移动平台运行环境的语义地图。
可以由无人机和/或其控制装置确定语义地图中目标图像区域的语义信息。
可以由无人机和/或其控制装置对多个辅助点进行排序。
可以由无人机和/或其控制装置更新辅助点的位置信息。
可以由无人机和/或其控制装置删除辅助点。
可以由无人机和/或其控制装置规划可移动平台从返航起始点移动到返航目标点的移动路径。
可以由控制装置接收语义地图更新信息。
可以由控制装置显示用户交互界面及多种与路径规划相关的信息。
可以由无人机通过传感器检测在飞行过程中的障碍物信息。
可以由无人机和/或其控制装置更新语义地图。
可以由控制装置接收用户操作，以生成控制杆量。
需要说明的是，上述各操作的执行主体仅为示例性说明，不能理解为对本申请的限定，可以由可移动平台、控制装置、云台或负载其中的一个独立完成，或其中的几个配合完成。例如，对于可移动平台是陆地机器人的情形 下，可以在陆地机器人上设置人机交互模块(如包括用于显示人机交互界面的显示器等)，用户可以直接在可移动平台展示的交互界面上获取用户操作，以获取辅助点、地图更新信息等。其中，独立完成包括主动或被动地、直接或间接地从其它设备获取相应数据以执行相应操作
本申请实施例提供的路径规划方法，提高了用户编辑移动路径的自由度，用户通过设置辅助点的形式，后台生成的移动路径更好的反应了用户的意图，本申请实施例可以把用户的经验和外部知识引入到路径规划过程中，为解决复杂地形下的路径规划提供了一种可行方案，做到了自动化规划与人工规划的平衡，较小的人工工作量，带来了极大的效率提升。同时，本申请实施例可以在一定程度上降低硬件成本，显然，如果用户的辅助点足够合理，机器人无需或只需少量配置探测障碍物的传感器等昂贵的硬件设备。
本申请实施例提供的路径规划方法，基于辅助点和语义地图提供的环境信息作为路径规划的至少部分依据，丰富了环境信息的来源，降低了对相关技术通过复杂的传感器感知环境信息的依赖。尤其是对于较稳定的环境，其语义地图可以复用，无需每次进行路径规划时都需要通过复杂的传感器感知环境信息以实时建图。此外，由于辅助点和语义地图中包括的环境信息可编辑，使得用户可根据实际场景编辑环境信息，提高了其应用的灵活性。另外，由于语义地图是预先制作的，减少了可移动平台作业时环境检测的计算量，有效降低了资源消耗。
本申请的另一方面提供了一种路径规划方法，用于规划可移动平台的移动路径。
图18为本申请另一实施例提供的路径规划方法的流程示意图。
如图18所示，该方法可以包括操作S1802～操作S1804。
在操作S1802，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的。
在操作S1804，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径。
可移动平台、运行环境、辅助点、用户对控制装置的操作等具体内容参考前面的实施例的相同部分。目标路径点可以为用户期望可移动平台移动至的路径点，如返航目标点等，此处不再做赘述。
本申请实施例提供的路径规划方法，给出在辅助点满足预设安全条件时，至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径的方案，能有效提升规划的移动路径的安全性。
例如，预设安全条件包括但不限于：辅助点与距离辅助点最近的障碍物的距离大于预设安全距离阈值。其中，障碍物可以是实体的障碍物，也可以是虚拟障碍物，例如用户选定的绕障区域或者电子围栏。
图19为本申请实施例提供的安全距离的示意图。
如图19所示，安全距离是针对可移动平台按照规划好的移动路径进行移动过程中，针对检测到的障碍物，需要控制可移动平台与该障碍物之间的距离大于安全距离。
例如，可移动平台可以基于规划好移动路径进行移动。在移动过程中，需要基于实时检测到的障碍物信息进行避障。但是，相对于不采用辅助点和/或语义地图进行路径规划的场景中，本实施例采取的传感器的复杂度可以大幅度降低。例如，相关技术在进行自动返航过程中，为了保证可移动平台的移动安全，可以采用诸如全向雷达以及诸如图像传感器等，而本申请的技术方案可以只采用双向雷达即可，在降低硬件成本的同时，也降低了机身重量、计算资源消耗和能源消耗等。
图20为本申请另一实施例提供的安全距离的示意图。
如图20所示，该安全距离可以如图中的双向箭头线段所示。其中，图20中所示的安全距离是针对语义地图中避障策略是绕行的图形区域(标号为1116的图形区域)与辅助点52之间的距离，辅助点52与该标号为1116的区域之间的距离需要大于安全距离阈值。
在一个实施例中，上述方法还包括：若辅助点的位置信息不满足预设安全条件，则更新辅助点的位置信息，以基于更新后的辅助点的位置信息规划可移动平台移动到目标路径点的移动路径。
在一个实施例中，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径包括：若辅助点的位置信息满足预设安全条件，则基于辅助点的位置信息规划可移动平台从起始路径点移动到目标路径点的移动路径。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，起始路径点为返航条件触发时可移动平台的位置点，返航条件包括以下至少之一：可移动平台的作业任务完成；可移动平台获取到控制装置发送的返航指令；可移动平台与控制装置断开通信连接的时间大于预设时间阈值；可移动平台的电池的剩余电量与可移动平台返航所需电量之差小于或等于预设电量阈值。
在一个实施例中，辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。
例如，辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，交互界面显示有可移动平台的运行环境的地图。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，地图包括语义地图，语义地图中各个图像区域的语义信息与可移动平台的避障策略具有对应关系。
在一个实施例中，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径包括：根据辅助点、目标路径点在语义地图中对应的位置信息，确定目标图像区域；至少基于辅助点的位置信息以及目标图像区域的语义信息对应的可移动平台的避障策略，规划可移动平台移动到目标路径点的移动路径。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，避障策略包括以下至少一种：绕行策略、上方通过或下方通过。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径，包括：若辅助点的位置信息满足预设安全条件，则连接辅助点和目标路径点，得到参考移动路径。
平滑参考移动路径得到移动路径，移动路径的平滑度满足可移动平台的机动要求。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，辅助点的数量为多个。
相应地，上述方法还包括：对多个辅助点进行排序；若辅助点的位置信 息满足预设安全条件，则连接辅助点和目标路径点，得到参考移动路径包括：若辅助点的位置信息满足预设安全条件，则按照排序依序连接至少一个辅助点和目标路径点，得到参考移动路径。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，对多个辅助点进行排序包括：按照获取多个辅助点的时间顺序对辅助点进行排序；或者按照多个辅助点和目标路径点的相对位置关系对多个辅助点进行排序。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径可以包括如下操作。
首先，至少基于辅助点的位置信息在可移动平台的运行环境中确定移动路径所在的目标三维区域；然后，在目标三维区域中确定中间路径点，以规划可移动平台途径中间路径点移动到目标路径点的移动路径。
具体内容参考前面的实施例的相同部分，此处不再做赘述。
在一个实施例中，在目标三维区域中确定中间路径点可以包括：优化目标损失函数以确定中间路径点的运动参数，中间路径点的运动参数至少包括位置参数。
图21为本申请实施例提供的路径规划装置的结构示意图。
如图21所示，该路径规划装置2100可以包括一个或多个处理器2110，该一个或多个处理器2110可以集成在一个处理单元中，也可以分别设置在多个处理单元中。计算机可读存储介质2120，用于存储一个或多个计算机程序2121，计算机程序在被处理器执行时，实现如上的路径规划方法。
例如，计算机程序在被处理器执行时，实现如下操作。
首先，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置信息是基于用户对控制装置的操作生成的。
然后，至少基于辅助点的位置信息规划可移动平台从返航起始点移动到返航目标点的移动路径。
又例如，计算机程序在被处理器执行时，实现如下操作。
首先，获取可移动平台的运行环境中辅助点的位置信息，辅助点的位置 信息是基于用户对控制装置的操作生成的。
然后，若辅助点的位置信息满足预设安全条件，则至少基于辅助点的位置信息规划可移动平台移动到目标路径点的移动路径。
其中，该路径规划装置2100可以被设置在一个执行主体中或分别设置在多个执行主体中。例如，对于可以实现本地控制功能的陆地机器人等的场景中，该路径规划装置2100可以被设置在该陆地机器人中，如该陆地机器人上设置有云台，云台上可以设置相机，陆地机器人的机体上设置有显示屏以便于与用户进行交互。又例如，对于可以使用非本地控制装置对可移动平台进行控制的场景中，该路径规划装置2100的至少部分可以被设置在控制装置中，如接受用户操作的相关功能被设置在控制装置中。该路径规划装置2100的至少部分可以被设置在可移动平台中，如信息传输功能、环境信息感测功能和联动控制功能等中至少一种。此外，该路径规划装置2100的至少部分可以被设置在负载中，如执行作业的相关功能等。
例如，处理单元可以包括现场可编程门阵列(Field－Programmable Gate Array，FPGA)或者一个或者多个ARM处理器。处理单元可以与非易失性计算机可读存储介质2120连接。与非易失性计算机可读存储介质2120可以存储由处理单元所执行的逻辑、代码及/或者计算机指令，用于执行一个或者多个步骤。非易失性计算机可读存储介质2120可以包括一个或者多个存储单元(可去除的介质或者外部存储器，如SD卡或者RAM)。在某些实施例中，传感器感测的数据可以直接传送并存储到非易失性计算机可读存储介质2120的存储单元中。非易失性计算机可读存储介质2120的存储单元可以存储由处理单元所执行的逻辑、代码及/或者计算机指令，以执行本案描述的各种方法的各个实施例。例如，处理单元可以用于执行指令，以导致处理单元的一个或者多个处理器执行上述描述的追踪功能。存储单元可以存储感测模块感测数据，该数据感测由处理单元所处理。在某些实施例中，非易失性计算机可读存储介质2120的存储单元可以存储处理单元产生的处理结果。
在某些实施例中，处理单元可以与控制模块连接，用以控制可移动平台的状态。例如，控制模块可以用于控制可移动平台的动力机构，以调整可移动平台相对于六个自由度的空间方位、速度及/或加速度。可选地或者相结合的，控制模块可以控制承载体，负载或者感测模块中的一个或者多个。
处理单元还可以与通讯模块连接，用以与一个或者多个外围设备(如终端、显示设备、或者其它远程控制设备)传送及/或者接收数据。这里可以利用任何合适的通讯方法，如有线通讯或者无线通讯。例如，通讯模块可以利用到一个或者多个局域网、广域网、红外线、无线电、Wi-Fi、点对点(P2P)网络、电信网络、云网络等。可选地，可以用到中继站，如信号塔、卫星、或者移动基站等。
上述各个部件之间可以是相互适配的。例如，一个或者多个部件位于可移动平台、承载体、负载、终端、感测系统、或者与前述各设备通讯的额外的外部设备上。在某些实施例中，处理单元及/或非易失性计算机可读介质中的一个或者多个可以位于不同的位置，如在可移动平台、承载体、负载、终端、感测系统、或者与前述各设备通讯的额外的外部设备以及前述的各种结合上。
此外，与可移动平台相适配的控制装置可以包括输入模块、处理单元、存储器、显示模块、以及通讯模块，所有这样的部件都是通过总线或者相似的网络相连接。
输入模块包括一个或者多个输入机制，以获取用户通过操作该输入模块产生的输入。输入机制包括一个或者多个操纵杆、开关、旋钮、滑动开关、按钮、拨号盘、触摸屏、小键盘、键盘、鼠标、声音控制、手势控制、惯性模块等。输入模块可以用于获取用户的输入，该输入用于控制可移动平台、承载体、负载、或者其中部件的任何方面。任何方面包括姿态、位置、方向、飞行、追踪等。例如，输入机制可以是用户手动设置一个或者多个位置，每个位置对应一个预设输入，以控制可移动平台。
在某些实施例中，输入机制可以由用户操作，以输入控制指令，控制可移动平台的运动。例如，用户可以利用旋钮、开关或者相似的输入机制，输入可移动平台的运动模式，如自动飞行、自动驾驶或者根据预设运动路径运动。又如，用户可以通过用某种方法倾斜控制装置，以控制可移动平台的位置、姿态、方向、或者其它方面。控制装置的倾斜可以由一个或者多个惯性传感器所侦测，并产生对应的运动指令。再如，用户可以利用上述输入机制调整负载的操作参数(如变焦)、负载的姿态(通过承载体)，或者可移动平台上的任何物体的其它方面。
在某些实施例中，输入机制可以由用户操作，以输入前述描述目标物信息。例如，用户可以利用旋钮、开关或者相似的输入机制，选择合适的追踪模式，如人工追踪模式或者自动追踪模式。用户也可以利用该输入机制选择所要追踪的特定目标物、执行的目标物类型信息、或者其它相似的信息。在各种实施例中，输入模块可以由不止一个设备所执行。例如，输入模块可以由带有操纵杆的标准远程控制器所执行。带有操纵杆的标准远程控制器连接到运行适合应用程序(“APP”)的移动设备(如智能手机)中，以产生可移动平台的控制指令。APP可以用于获取用户的输入。
处理单元可以与存储器连接。存储器包括易失性或者非易失性存储介质，用于存储数据，及/或处理单元可执行的逻辑、代码、及/或程序指令，用于执行一个或者多个规则或者功能。存储器可以包括一个或者多个存储单元(可去除的介质或者外部存储器，如SD卡或者RAM)。在某些实施例中，输入模块的数据可以直接传送并存储在存储器的存储单元中。存储器的存储单元可以存储由处理单元所执行的逻辑、代码及/或者计算机指令，以执行本案描述的各种方法的各个实施例。例如，处理单元可以用于执行指令，以导致处理单元的一个或者多个处理器处理及显示从可移动平台获取的感应数据(如影像)，基于用户输入产生的控制指令，包括运动指令及目标物信息，并导致通讯模块传送及/或者接收数据等。存储单元可以存储感测数据或者从外部设备(如可移动平台)接收的其它数据。在某些实施例中，存储器的存储单元可以存储处理单元生成的处理结果。
在某些实施例中，显示模块可以用于显示如图2中可移动平台10、承载体13及/或作业设备关于位置、平移速度、平移加速度、方向、角速度、角加速度、或者其结合等的信息。显示模块可以用于获取可移动平台及/或者负载发送的信息，如感测数据(相机或者其它影像捕获设备记录的影像)、所描述的追踪数据、控制反馈数据等。在某些实施例中，显示模块可以与输入模块由相同的设备所执行。在其它实施例中，显示模块与输入模块可以由不相同的设备所执行。
通讯模块可以用于从一个或者多个远程设备(如可移动平台、承载体、基站等)传送及/或者接收数据。例如，通讯模块可以传送控制信号(如运动信号、目标物信息、追踪控制指令)给外围系统或者设备，如图2中可移动 平台10、承载体13及/或作业设备14。通讯模块可以包括传送器及接收器，分别用于从远程设备接收数据以及传送数据给远程设备。在某些实施例中，通讯模块可以包括收发器，其结合了传送器与接收器的功能。在某些实施例中，传送器与接收器之间以及与处理单元之间可以彼此通讯。通讯可以利用任何合适的通讯手段，如有线通讯或者无线通讯。
可移动平台在运动过程中捕获的影像可以从可移动平台或者影像设备传回给控制装置或者其它适合的设备，以显示、播放、存储、编辑或者其它目的。这样的传送可以是当影像设备捕获影像时，实时的或者将近实时的发生。可选地，影像的捕获及传送之间可以有延迟。在某些实施例中，影像可以存储在可移动平台的存储器中，而不用传送到任何其它地方。用户可以实时看到这些影像，如果需要，调整目标物信息或者调整可移动平台或者其部件的其它方面。调整的目标物信息可以提供给可移动平台，重复的过程可能继续直到获得可想要的影像。在某些实施例中，影像可以从可移动平台、影像设备及/或控制装置传送给远程服务器。例如，影像可以在一些社交网络平台，如微信朋友圈或者微博上以进行分享。
在一个实施例中，返航起始点为返航条件触发时可移动平台的位置点，返航条件包括以下至少之一：
可移动平台的作业任务完成。
可移动平台获取到控制装置发送的返航指令。
可移动平台与控制装置断开通信连接的时间大于预设时间阈值。
可移动平台的电池的剩余电量与可移动平台返航所需电量之差小于或等于预设电量阈值。
此外，该路径规划装置中各模块可以实现的功能、操作等，可以参考前面与方法部分对应的实施例的内容，此处不再做赘述。
本申请的另一方面还提供了一种路径规划系统，用于规划移动路径，其中，系统包括：相互通信连接的控制装置和可移动平台，其中：控制装置和/或可移动平台包括如上的路径规划装置。
其中，可移动平台具体可以是农业无人机或农业无人车等。
图22为本申请实施例提供的可移动平台的结构示意图。
如图22所示，该可移动平台是无人机220，该无人机可以包括多个动力机构221，以驱动无人机220飞行。
以上为本申请的最优实施例，需要说明的，该最优的实施例仅用于理解本申请，并不用于限制本申请的保护范围。并且，最优实施例中的特征，在无特别注明的情况下，均同时适用于方法实施例和装置实施例，在相同或不同实施例中出现的技术特征在不相互冲突的情况下可以组合使用。
在一些可能的实施例中，最后应说明的是：以上实施方式仅用以说明本申请的技术方案，而非对其进行限制；尽管参照前述实施方式对本申请已经进行了详细的说明，但本领域的普通技术人员应当理解：其依然可以对前述实施方式所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请实施方式技术方案的范围。

Claims (62)

  1. 一种路径规划方法，用于规划可移动平台的移动路径，其特征在于，所述方法包括：
    获取所述可移动平台的运行环境中辅助点的位置信息，所述辅助点的位置信息是基于用户对控制装置的操作生成的；
    至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  2. 根据权利要求1所述的方法，其特征在于，所述返航起始点为返航条件触发时可移动平台的位置点，所述返航条件包括以下至少之一：
    所述可移动平台的作业任务完成；
    所述可移动平台获取到所述控制装置发送的返航指令；
    所述可移动平台与所述控制装置断开通信连接的时间大于预设时间阈值；
    所述可移动平台的电池的剩余电量与所述可移动平台返航所需电量之差小于或等于预设电量阈值。
  3. 根据权利要求1所述的方法，其特征在于，所述辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。
  4. 根据权利要求1所述的方法，其特征在于，所述辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，所述交互界面显示有所述可移动平台的运行环境的地图。
  5. 根据权利要求4所述的方法，其特征在于，所述地图包括语义地图，所述语义地图中各个图像区域的语义信息与所述可移动平台的避障策略具有对应关系。
  6. 根据权利要求5所述的方法，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    根据所述辅助点、所述返航起始点、所述返航目标点在所述语义地图中对应的位置信息，确定目标图像区域；
    至少基于所述辅助点的位置信息以及所述目标图像区域的语义信息对应的可移动平台的避障策略，规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  7. 根据权利要求5所述的方法，其特征在于，所述避障策略包括以下至少一种：绕行策略、上方通过或下方通过。
  8. 根据权利要求1所述的方法，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    连接所述返航起始点、所述辅助点和所述返航目标点，得到参考移动路径；
    平滑所述参考移动路径得到所述移动路径，所述移动路径的平滑度满足所述可移动平台的机动要求。
  9. 根据权利要求8所述的方法，其特征在于，所述辅助点的数量为多个；
    所述方法还包括：对多个所述辅助点进行排序；
    所述连接所述返航起始点、所述辅助点和所述返航目标点，得到参考移动路径，包括：
    按照所述排序依序连接返航起始点、多个所述辅助点和所述返航目标点，得到参考移动路径。
  10. 根据权利要求9所述的方法，其特征在于，所述对多个所述辅助点进行排序，包括：
    按照获取多个所述辅助点的时间顺序对所述辅助点进行排序；或者
    按照多个所述辅助点和所述返航起始点或所述返航目标点的相对位置关系对多个所述辅助点进行排序。
  11. 根据权利要求1所述的方法，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    至少基于所述辅助点的位置信息在所述可移动平台的运行环境中确定所述移动路径所在的目标三维区域；
    在所述目标三维区域中确定中间路径点，以规划所述可移动平台从返航起始点途径所述中间路径点移动到返航目标点的移动路径。
  12. 根据权利要求11所述的方法，其特征在于，所述在所述目标三维区域中确定中间路径点，包括：
    优化目标损失函数以确定所述中间路径点的运动参数，所述中间路径点的运动参数至少包括位置参数。
  13. 根据权利要求1所述的方法，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  14. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    若所述辅助点的位置信息不满足预设安全条件，则更新所述辅助点的位置信息，以至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  15. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    若所述辅助点的位置信息不满足预设安全条件，则删除所述辅助点的位置信息。
  16. 根据权利要求13所述的方法，其特征在于，所述预设安全条件包括：所述辅助点与距离辅助点最近的障碍物的距离大于预设安全距离阈值。
  17. 一种路径规划方法，用于规划可移动平台的移动路径，其特征在于，所述方法包括：
    获取所述可移动平台的运行环境中辅助点的位置信息，所述辅助点的位置信息是基于用户对控制装置的操作生成的；
    若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径。
  18. 根据权利要求17所述的方法，其特征在于，还包括：
    若所述辅助点的位置信息不满足预设安全条件，则更新所述辅助点的位置信息，以基于更新后的辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径。
  19. 根据权利要求17所述的方法，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台从起始路径点移动到目标路径点的移动路径。
  20. 根据权利要求17所述的方法，其特征在于，所述起始路径点为返航条件触发时可移动平台的位置点，所述返航条件包括以下至少之一：
    所述可移动平台的作业任务完成；
    所述可移动平台获取到所述控制装置发送的返航指令；
    所述可移动平台与所述控制装置断开通信连接的时间大于预设时间阈值；
    所述可移动平台的电池的剩余电量与所述可移动平台返航所需电量之差小于或等于预设电量阈值。
  21. 根据权利要求17所述的方法，其特征在于，所述辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。
  22. 根据权利要求17所述的方法，其特征在于，所述辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，所述交互界面显示有所述可移动平台的运行环境的地图。
  23. 根据权利要求22所述的方法，其特征在于，所述地图包括语义地图，所述语义地图中各个图像区域的语义信息与所述可移动平台的避障策略具有对应关系。
  24. 根据权利要求23所述的方法，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：
    根据所述辅助点、所述目标路径点在所述语义地图中对应的位置信息，确定目标图像区域；
    至少基于所述辅助点的位置信息以及所述目标图像区域的语义信息对应的可移动平台的避障策略，规划所述可移动平台移动到目标路径点的移动路径。
  25. 根据权利要求24所述的方法，其特征在于，所述避障策略包括以下至少一种：绕行策略、上方通过或下方通过。
  26. 根据权利要求17所述的方法，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径，包括：
    若所述辅助点的位置信息满足预设安全条件，则连接所述辅助点和所述目标路径点，得到参考移动路径；
    平滑所述参考移动路径得到所述移动路径，所述移动路径的平滑度满足所述可移动平台的机动要求。
  27. 根据权利要求26所述的方法，其特征在于，所述辅助点的数量为多个；
    所述方法还包括：对多个所述辅助点进行排序；
    所述若所述辅助点的位置信息满足预设安全条件，则连接所述辅助点和所述目标路径点，得到参考移动路径包括：
    若所述辅助点的位置信息满足预设安全条件，则按照所述排序依序连接至少一个所述辅助点和所述目标路径点，得到参考移动路径。
  28. 根据权利要求27所述的方法，其特征在于，所述对多个所述辅助点进行排序包括：
    按照获取多个所述辅助点的时间顺序对所述辅助点进行排序；或者
    按照多个所述辅助点和所述目标路径点的相对位置关系对多个所述辅助点进行排序。
  29. 根据权利要求17所述的方法，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：
    至少基于所述辅助点的位置信息在所述可移动平台的运行环境中确定所述移动路径所在的目标三维区域；
    在所述目标三维区域中确定中间路径点，以规划所述可移动平台途径所述中间路径点移动到目标路径点的移动路径。
  30. 根据权利要求29所述的方法，其特征在于，所述在所述目标三维区域中确定中间路径点包括：
    优化目标损失函数以确定所述中间路径点的运动参数，所述中间路径点的运动参数至少包括位置参数。
  31. 一种路径规划装置，用于规划可移动平台的移动路径，其特征在于，所述装置包括：
    一个或多个处理器；以及
    计算机可读存储介质，用于存储一个或多个计算机程序，所述计算机程序在被所述处理器执行时，实现：
    获取所述可移动平台的运行环境中辅助点的位置信息，所述辅助点的位置信息是基于用户对控制装置的操作生成的；
    至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  32. 根据权利要求31所述的装置，其特征在于，所述返航起始点为返航条件触发时可移动平台的位置点，所述返航条件包括以下至少之一：
    所述可移动平台的作业任务完成；
    所述可移动平台获取到所述控制装置发送的返航指令；
    所述可移动平台与所述控制装置断开通信连接的时间大于预设时间阈值；
    所述可移动平台的电池的剩余电量与所述可移动平台返航所需电量之差小于或等于预设电量阈值。
  33. 根据权利要求32所述的装置，其特征在于，所述辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。
  34. 根据权利要求33所述的装置，其特征在于，
    所述辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，所述交互界面显示有所述可移动平台的运行环境的地图。
  35. 根据权利要求34所述的装置，其特征在于，所述地图包括语义地图，所述语义地图中各个图像区域的语义信息与所述可移动平台的避障策略具有对应关系。
  36. 根据权利要求35所述的装置，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    根据所述辅助点、所述返航起始点、所述返航目标点在所述语义地图中对应的位置信息，确定目标图像区域；
    至少基于所述辅助点的位置信息以及所述目标图像区域的语义信息对应的可移动平台的避障策略，规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  37. 根据权利要求35所述的装置，其特征在于，所述避障策略包括以下至少一种：绕行策略、上方通过或下方通过。
  38. 根据权利要求31所述的装置，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    连接所述返航起始点、所述辅助点和所述返航目标点，得到参考移动路径；
    平滑所述参考移动路径得到所述移动路径，所述移动路径的平滑度满足所述可移动平台的机动要求。
  39. 根据权利要求38所述的装置，其特征在于，所述辅助点的数量为多个；
    所述装置还包括：对多个所述辅助点进行排序；
    所述连接所述返航起始点、所述辅助点和所述返航目标点，得到参考移动路径，包括：
    按照所述排序依序连接返航起始点、多个所述辅助点和所述返航目标点，得到参考移动路径。
  40. 根据权利要求39所述的装置，其特征在于，所述对多个所述辅助点进行排序，包括：
    按照获取多个所述辅助点的时间顺序对所述辅助点进行排序；或者
    按照多个所述辅助点和所述返航起始点或所述返航目标点的相对位置关系对多个所述辅助点进行排序。
  41. 根据权利要求31所述的装置，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    至少基于所述辅助点的位置信息在所述可移动平台的运行环境中确定所述移动路径所在的目标三维区域；
    在所述目标三维区域中确定中间路径点，以规划所述可移动平台从返航起始点途径所述中间路径点移动到返航目标点的移动路径。
  42. 根据权利要求41所述的装置，其特征在于，所述在所述目标三维区域中确定中间路径点，包括：
    优化目标损失函数以确定所述中间路径点的运动参数，所述中间路径点的运动参数至少包括位置参数。
  43. 根据权利要求31所述的装置，其特征在于，所述至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径，包括：
    若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到返航目标点的移动路径。
  44. 根据权利要求43所述的装置，其特征在于，所述装置还包括：
    若所述辅助点的位置信息不满足预设安全条件，则更新所述辅助点的位置信息，以至少基于所述辅助点的位置信息规划所述可移动平台从返航起始点移动到返航目标点的移动路径。
  45. 根据权利要求43所述的装置，其特征在于，所述装置还包括：
    若所述辅助点的位置信息不满足预设安全条件，则删除所述辅助点的位置信息。
  46. 根据权利要求43所述的装置，其特征在于，所述预设安全条件包括：所述辅助点与距离辅助点最近的障碍物的距离大于预设安全距离阈值。
  47. 一种路径规划装置，用于规划可移动平台的移动路径，其特征在于，所述装置包括：
    获取所述可移动平台的运行环境中辅助点的位置信息，所述辅助点的位置信息是基于用户对控制装置的操作生成的；
    若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径。
  48. 根据权利要求47所述的装置，其特征在于，还包括：
    若所述辅助点的位置信息不满足预设安全条件，则更新所述辅助点的位置信息，以基于更新后的辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径。
  49. 根据权利要求47所述的装置，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：若所述辅助点的位置信息满足预设安全条件，则基于所述辅助点的位置信息规划所述可移动平台从起始路径点移动到目标路径点的移动路径。
  50. 根据权利要求47所述的装置，其特征在于，所述起始路径点为返航条件触发时可移动平台的位置点，所述返航条件包括以下至少之一：
    所述可移动平台的作业任务完成；
    所述可移动平台获取到所述控制装置发送的返航指令；
    所述可移动平台与所述控制装置断开通信连接的时间大于预设时间阈值；
    所述可移动平台的电池的剩余电量与所述可移动平台返航所需电量之差小于或等于预设电量阈值。
  51. 根据权利要求47所述的装置，其特征在于，所述辅助点的位置信息是基于用户对控制装置的配置文件的操作生成的。
  52. 根据权利要求47所述的装置，其特征在于，所述辅助点的位置信息是基于用户对控制装置的交互界面的操作生成的，所述交互界面显示有所述可移动平台的运行环境的地图。
  53. 根据权利要求52所述的装置，其特征在于，所述地图包括语义地图，所述语义地图中各个图像区域的语义信息与所述可移动平台的避障策略具有对应关系。
  54. 根据权利要求53所述的装置，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：
    根据所述辅助点、所述目标路径点在所述语义地图中对应的位置信息，确定目标图像区域；
    至少基于所述辅助点的位置信息以及所述目标图像区域的语义信息对应的可移动平台的避障策略，规划所述可移动平台移动到目标路径点的移动路径。
  55. 根据权利要求54所述的装置，其特征在于，所述避障策略包括以下至少一种：绕行策略、上方通过或下方通过。
  56. 根据权利要求47所述的装置，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径，包括：
    若所述辅助点的位置信息满足预设安全条件，则连接所述辅助点和所述目标路径点，得到参考移动路径；
    平滑所述参考移动路径得到所述移动路径，所述移动路径的平滑度满足所述可移动平台的机动要求。
  57. 根据权利要求56所述的装置，其特征在于，所述辅助点的数量为多个；
    所述装置还包括：对多个所述辅助点进行排序；
    所述若所述辅助点的位置信息满足预设安全条件，则连接所述辅助点和所述目标路径点，得到参考移动路径包括：
    若所述辅助点的位置信息满足预设安全条件，则按照所述排序依序连接至少一个所述辅助点和所述目标路径点，得到参考移动路径。
  58. 根据权利要求57所述的装置，其特征在于，所述对多个所述辅助点进行排序包括：
    按照获取多个所述辅助点的时间顺序对所述辅助点进行排序；或者
    按照多个所述辅助点和所述目标路径点的相对位置关系对多个所述辅助点进行排序。
  59. 根据权利要求47所述的装置，其特征在于，所述若所述辅助点的位置信息满足预设安全条件，则至少基于所述辅助点的位置信息规划所述可移动平台移动到目标路径点的移动路径包括：
    至少基于所述辅助点的位置信息在所述可移动平台的运行环境中确定所述移动路径所在的目标三维区域；
    在所述目标三维区域中确定中间路径点，以规划所述可移动平台途径所述中间路径点移动到目标路径点的移动路径。
  60. 根据权利要求59所述的装置，其特征在于，所述在所述目标三维区域中确定中间路径点包括：
    优化目标损失函数以确定所述中间路径点的运动参数，所述中间路径点的运动参数至少包括位置参数。
  61. 一种路径规划系统，用于规划移动路径，其特征在于，所述系统包括：相互通信连接的控制装置和可移动平台，其中：
    所述控制装置和/或所述可移动平台包括权利要求31-60任一项所述的路径规划装置。
  62. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被处理器执行以实现权利要求1-30中任一项所述的方法。
PCT/CN2020/127634 2020-11-09 2020-11-09 路径规划方法、路径规划装置、路径规划系统和介质 WO2022095067A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202080073942.6A CN114746719A (zh) 2020-11-09 2020-11-09 路径规划方法、路径规划装置、路径规划系统和介质
PCT/CN2020/127634 WO2022095067A1 (zh) 2020-11-09 2020-11-09 路径规划方法、路径规划装置、路径规划系统和介质

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/127634 WO2022095067A1 (zh) 2020-11-09 2020-11-09 路径规划方法、路径规划装置、路径规划系统和介质

Publications (1)

Publication Number Publication Date
WO2022095067A1 true WO2022095067A1 (zh) 2022-05-12

Family

ID=81458550

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/127634 WO2022095067A1 (zh) 2020-11-09 2020-11-09 路径规划方法、路径规划装置、路径规划系统和介质

Country Status (2)

Country Link
CN (1) CN114746719A (zh)
WO (1) WO2022095067A1 (zh)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116225072A (zh) * 2023-05-09 2023-06-06 济宁市兖州区同瑞机械有限公司 一种适用于农业运输机的路线实时规划管理系统
CN116643518A (zh) * 2023-05-26 2023-08-25 杭州蓝海拓凡科技有限公司 一种智能化电力环境检测的机器人管控系统
CN117075484A (zh) * 2023-10-18 2023-11-17 山东科技大学 一种水下无人器返航路径规划方法
CN118151668A (zh) * 2024-05-08 2024-06-07 中航(成都)无人机系统股份有限公司 基于电子围栏区域的飞行器控制方法、装置、设备及介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104881039A (zh) * 2015-05-12 2015-09-02 零度智控（北京）智能科技有限公司 一种无人机返航的方法及系统
CN109062258A (zh) * 2018-10-08 2018-12-21 杭州瓦屋科技有限公司 控制无人机返航方法和装置
CN109101041A (zh) * 2018-10-22 2018-12-28 深圳市智璟科技有限公司 一种无人飞机的动态跟随及动态返航方法
CN109253729A (zh) * 2018-09-19 2019-01-22 沈阳无距科技有限公司 一种无人机航线规划方法、装置及电子设备
US10249200B1 (en) * 2016-07-22 2019-04-02 Amazon Technologies, Inc. Deployable delivery guidance
CN109917799A (zh) * 2019-03-06 2019-06-21 特斯联（北京）科技有限公司 应用于景区空中观光的载人无人机飞行方法及系统

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104881039A (zh) * 2015-05-12 2015-09-02 零度智控（北京）智能科技有限公司 一种无人机返航的方法及系统
US10249200B1 (en) * 2016-07-22 2019-04-02 Amazon Technologies, Inc. Deployable delivery guidance
CN109253729A (zh) * 2018-09-19 2019-01-22 沈阳无距科技有限公司 一种无人机航线规划方法、装置及电子设备
CN109062258A (zh) * 2018-10-08 2018-12-21 杭州瓦屋科技有限公司 控制无人机返航方法和装置
CN109101041A (zh) * 2018-10-22 2018-12-28 深圳市智璟科技有限公司 一种无人飞机的动态跟随及动态返航方法
CN109917799A (zh) * 2019-03-06 2019-06-21 特斯联（北京）科技有限公司 应用于景区空中观光的载人无人机飞行方法及系统

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116225072A (zh) * 2023-05-09 2023-06-06 济宁市兖州区同瑞机械有限公司 一种适用于农业运输机的路线实时规划管理系统
CN116643518A (zh) * 2023-05-26 2023-08-25 杭州蓝海拓凡科技有限公司 一种智能化电力环境检测的机器人管控系统
CN117075484A (zh) * 2023-10-18 2023-11-17 山东科技大学 一种水下无人器返航路径规划方法
CN117075484B (zh) * 2023-10-18 2024-01-30 山东科技大学 一种水下无人器返航路径规划方法
CN118151668A (zh) * 2024-05-08 2024-06-07 中航(成都)无人机系统股份有限公司 基于电子围栏区域的飞行器控制方法、装置、设备及介质

Also Published As

Publication number Publication date
CN114746719A (zh) 2022-07-12

Similar Documents

Publication Publication Date Title
US11932392B2 (en) Systems and methods for adjusting UAV trajectory
WO2022095067A1 (zh) 路径规划方法、路径规划装置、路径规划系统和介质
WO2022095060A1 (zh) 路径规划方法、路径规划装置、路径规划系统和介质
CN110325939B (zh) 用于操作无人驾驶飞行器的系统和方法
US11460844B2 (en) Unmanned aerial image capture platform
EP3662335B1 (en) Model for determining drop-off spot at delivery location
CN108521787B (zh) 一种导航处理方法、装置及控制设备
JP2022184945A (ja) 航空機のスマート着陸
US11644839B2 (en) Systems and methods for generating a real-time map using a movable object
US20160116912A1 (en) System and method for controlling unmanned vehicles
WO2016033797A1 (en) Multi-sensor environmental mapping
CN111051198B (zh) 无人飞行器控制系统、无人飞行器控制方法、及程序
WO2021081960A1 (zh) 一种航线规划方法、设备、系统及存储介质
WO2020107454A1 (zh) 障碍物的精准确定方法、设备及计算机可读存储介质
WO2022226720A1 (zh) 路径规划方法、路径规划装置和介质
CN113841381B (zh) 视场确定方法、视场确定装置、视场确定系统和介质
Weaver Collaborative coordination and control for an implemented heterogeneous swarm of uavs and ugvs
EP4024155B1 (en) Method, system and computer program product of control of unmanned aerial vehicles
US20240053746A1 (en) Display system, communications system, display control method, and program
JP2021036452A (ja) Ｕａｖ軌道を調整するシステム及び方法
Lee UNIT 45002 APO AP 96338-5002

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20960524

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20960524

Country of ref document: EP

Kind code of ref document: A1