WO2022089159A1 - 困境规避方法、自主移动设备和存储介质 - Google Patents

困境规避方法、自主移动设备和存储介质 Download PDF

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Publication number
WO2022089159A1
WO2022089159A1 PCT/CN2021/122429 CN2021122429W WO2022089159A1 WO 2022089159 A1 WO2022089159 A1 WO 2022089159A1 CN 2021122429 W CN2021122429 W CN 2021122429W WO 2022089159 A1 WO2022089159 A1 WO 2022089159A1
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Prior art keywords
mobile device
autonomous mobile
area
location
sensing information
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PCT/CN2021/122429
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English (en)
French (fr)
Inventor
吴欣
刘章林
张一茗
陈震
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速感科技（北京）有限公司
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Publication of WO2022089159A1 publication Critical patent/WO2022089159A1/zh
Priority to US18/309,758 priority Critical patent/US20230266765A1/en

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    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • 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
    • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804—Creation or updating of map data
    • G01C21/3807—Creation or updating of map data characterised by the type of data
    • G01C21/3815—Road data
    • 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
    • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804—Creation or updating of map data
    • G01C21/3833—Creation or updating of map data characterised by the source of data
    • G01C21/3837—Data obtained from a single source

Definitions

  • the present application relates to intelligent control technology, and in particular, to a dilemma avoidance method, an autonomous mobile device and a storage medium.
  • Autonomous mobile devices usually move autonomously to perform various tasks on the ground in a limited space, and the ground in the limited space can be called the work area of autonomous mobile devices.
  • the work area of autonomous mobile devices can be called the work area of autonomous mobile devices.
  • the environment in its work area is also different.
  • the environment in the work area of many autonomous mobile devices is complex, which may hinder the operation of autonomous mobile devices.
  • the autonomous mobile device cannot avoid these obstacles well during the operation process, resulting in interruption of operation, reduced work efficiency of the autonomous mobile device, or even damage to the device.
  • the present application provides a dilemma avoidance method, an autonomous mobile device and a storage medium.
  • the autonomous mobile device can identify obstacles that may be encountered by itself, build a dangerous area, avoid the dangerous area during operation, and reduce or even avoid being blocked. Improve the working efficiency of equipment.
  • the present application provides a dilemma avoidance method, which is applied to an autonomous mobile device, and the method includes:
  • the autonomous mobile device operates in the work area
  • the sensing information can be used to obtain the environmental state of the location of the autonomous mobile device when acquiring the sensing information or a relationship with the autonomous mobile device The environmental state at the location where the sensing information is obtained from the detection distance;
  • the sensing information determine whether the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at a detection distance from the location where the autonomous mobile device is acquiring the sensing information is predicament;
  • the predicament is determined as a dilemma.
  • the corresponding location is determined as a hazardous location
  • Hazardous areas are marked in the map of the work area according to the hazardous location.
  • marking the dangerous area in the map of the working area according to the dangerous location includes:
  • the method further includes:
  • marking the dangerous area in the map of the working area according to the dangerous location includes:
  • the danger area is marked on the map of the work area with a corresponding mark symbol.
  • the determining the danger category of the danger area includes:
  • the hazard class of the hazardous area is determined.
  • the types of the dangerous areas include: high-risk areas and low-risk areas;
  • the dangerous area is marked on the map of the work area with corresponding marking symbols according to the danger category of the dangerous area, including:
  • the category of the dangerous area is a high-risk area, directly mark the dangerous area on the map of the work area with the corresponding marking symbol;
  • the dangerous area is sent to the user terminal, so that the user can determine whether to mark it in the map of the working area.
  • the method further includes:
  • the acquiring sensing information collected by at least one sensor of the autonomous mobile device includes:
  • the sensing information determine the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at a detection distance from the location where the autonomous mobile device is acquiring the sensing information Is it a dilemma, including:
  • the distance is greater than or equal to the preset distance, it is determined that the environmental state of the location where the autonomous mobile device is located when the distance is acquired is a difficult situation.
  • the acquiring sensing information collected by at least one sensor of the autonomous mobile device includes:
  • the sensing information determine the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at a detection distance from the location where the autonomous mobile device is acquiring the sensing information Is it a dilemma, including:
  • the environmental state of the location where the autonomous mobile device is located is dilemma.
  • an autonomous mobile device including:
  • Get module used to get the map of the work area
  • the acquisition module is further configured to acquire sensing information collected by at least one sensor of the autonomous mobile device, and the sensing information is used to obtain the location of the autonomous mobile device when acquiring the sensing information.
  • the environmental state or the environmental state at a detection distance from the location where the autonomous mobile device obtained the sensing information;
  • a processing module configured to determine, according to the sensing information, the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or a detection distance from the location where the autonomous mobile device is located when acquiring the sensing information Whether the environmental state of the autonomous mobile device is a predicament; if it is determined that the environmental state of the location of the autonomous mobile device when acquiring the sensing information or the environmental state at the detection distance from the location of the autonomous mobile device when acquiring the sensing information is: Dilemma, the position corresponding to the dilemma is determined as a dangerous position;
  • the marking module is used for marking the dangerous area in the map of the working area according to the dangerous location.
  • the marking module marks the dangerous area in the map of the working area according to the dangerous location, it is specifically used for:
  • the device further includes: an update module configured to update the dangerous area in the historical map according to the dangerous area in the current map of the work area.
  • the marking module marks the dangerous area in the map of the working area according to the dangerous location, it is specifically used for:
  • the danger area is marked on the map of the work area with a corresponding mark symbol.
  • the marking module determines the danger category of the danger area, it is specifically used for:
  • the hazard class of the hazardous area is determined.
  • the types of the dangerous areas include: high-risk areas and low-risk areas;
  • the marking module marks the dangerous area on the map of the working area with a corresponding marking symbol according to the danger category of the dangerous area, it is specifically used for:
  • the category of the dangerous area is a high-risk area, directly mark the dangerous area on the map of the work area with the corresponding marking symbol;
  • the dangerous area is sent to the user terminal, so that the user can determine whether to mark it in the map of the working area.
  • the obtaining module is also used for: obtaining work tasks;
  • the processing module is further configured to perform path planning according to the work task and the determined dangerous area;
  • the running module is used to move according to the planned path.
  • the acquisition module acquires the sensing information collected by at least one sensor of the autonomous mobile device, it is specifically used for:
  • the processing module judges, according to the sensing information, the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the detection distance from the location where the autonomous mobile device is acquiring the sensing information.
  • the environmental state of is a dilemma, it is specifically used for:
  • the distance is greater than or equal to the preset distance, it is determined that the environmental state of the location where the autonomous mobile device is located when the distance is acquired is a difficult situation.
  • the acquisition module acquires the sensing information collected by at least one sensor of the autonomous mobile device, it is specifically used for:
  • the processing module judges, according to the sensing information, the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the detection distance from the location where the autonomous mobile device is acquiring the sensing information.
  • the environmental state of is a dilemma, it is specifically used for:
  • the environmental state of the location where the autonomous mobile device is located is dilemma.
  • the present application provides an autonomous mobile device, comprising: a memory for storing program instructions; and a processor for calling and executing the program instructions in the memory to execute the method described in the first aspect.
  • the present application provides a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the method described in the first aspect is implemented.
  • the present application provides a computer program, comprising program code, when a computer runs the computer program, the program code executes the method according to the first aspect.
  • the present application provides a program product, the program product includes a computer program, the computer program is stored in a readable storage medium, and a processor of an autonomous mobile device can read the computer program from the readable storage medium A computer program executed by the processor to cause an autonomous mobile device to implement the method of the first aspect.
  • the present application provides a dilemma avoidance method, autonomous mobile device and storage medium.
  • the dilemma avoidance method is applied to an autonomous mobile device, and the method includes: acquiring a map of a work area; the autonomous mobile device operates in the work area; acquiring sensor data collected by at least one sensor of the autonomous mobile device
  • the sensing information can be used to obtain the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the detection distance from the location where the autonomous mobile device is acquiring the sensing information.
  • Environmental state determine the environmental state of the location of the autonomous mobile device when acquiring the sensing information or the environment at a detection distance from the location of the autonomous mobile device when acquiring the sensing information Whether the state is a predicament; if it is determined that the environmental state of the location of the autonomous mobile device when acquiring the sensing information or the environmental state at a detection distance from the location of the autonomous mobile device when acquiring the sensing information is a predicament, Then, the position corresponding to the dilemma is determined as a dangerous position; the dangerous area is marked in the map of the working area according to the dangerous position.
  • sensors installed in autonomous mobile devices.
  • the sensing information collected by the sensors it is basically possible to determine the operating state or the environment in which the device collects the sensing information, and then determine whether it is facing potential danger, so as to determine whether the device collects the sensing information. Whether the location of the sensor information is a dangerous location, so as to detect the dangerous area in time and try to avoid the dangerous area during the movement process, reduce or even avoid the situation of being hindered, and improve the working efficiency of the equipment.
  • FIG. 1 is a schematic diagram of an application scenario provided by the present application.
  • FIG. 4 is a flowchart of another dilemma avoidance method provided by an embodiment of the present application.
  • FIG. 5A is a schematic diagram of navigation provided by an embodiment of the present application.
  • FIG. 5B is a schematic diagram of navigation provided by an embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of an autonomous mobile device according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of an autonomous mobile device according to an embodiment of the present application.
  • Autonomous mobile devices refer to smart devices that autonomously perform preset tasks within a set area.
  • autonomous mobile devices usually include but are not limited to cleaning robots (such as smart sweepers, smart floor mopping machines, window cleaning robots, etc.), companion mobile robots (such as smart electronic pets, nanny robots, etc.), service mobile robots (such as Reception robots in hotels, hotels, meeting places), industrial inspection intelligent equipment (such as power inspection robots, intelligent forklifts, etc.), security robots (such as household or commercial intelligent security robots), etc.
  • Autonomous mobile devices usually move autonomously on the ground in a limited space to perform various tasks. For example, cleaning robots and companion mobile robots usually operate on indoor ground, while service mobile robots usually operate on the ground in hotels, conference venues and other spaces. run.
  • the ground in this limited space can be called the working area of the autonomous mobile device.
  • dilemma refers to various obstacles in the work area that hinder the autonomous mobile device from moving on the ground, making it impossible or difficult for it to escape from the area, or various structures such as protrusions and depressions, or may hinder autonomous movement.
  • Various obstacles and environmental conditions that may cause damage to the device itself or the ground, or may bring danger to users. Since the predicament in the working area usually occupies a certain range, for example, the range occupied by the lamp holder is the area occupied by the lamp holder on the ground, and the area occupied by the dense area of desks and chairs can be equal to the area enclosed by the outermost table and chair legs.
  • the area occupied by the dilemma constitutes the least dangerous zone. Therefore, in this application, the location where the autonomous mobile device encounters a difficult situation is called a dangerous location; the ground area corresponding to the area where the difficult situation is located is called a dangerous area.
  • objects or structures with height differences such as steps or stairs may cause fall damage to autonomous mobile devices, then steps or stairs are a type of predicament, and the location of steps or stairs is a hazardous location or hazardous area; lamp sockets, fan sockets
  • the raised structure with the same height above the ground may cause the autonomous mobile device to be padded and the wheels will idle, so the lamp holder and the fan holder are a kind of predicament, and the location of the lamp holder and the fan holder is a dangerous location or dangerous area;
  • the uneven and narrow gaps such as guide rails may cause the wheels of the autonomous mobile device to be stuck, so it is also a kind of predicament; particularly smooth ground or ground with accumulated water may cause the wheels of the autonomous mobile device to slip, causing the wheels of the autonomous mobile
  • the mileage calculated by the code disc is inaccurate, so it is also a kind of dilemma; the ropes and other hanging objects such as floor-to-ceiling curtains are dragged on the ground, which may entangle the wheels of the autonomous mobile device and make them unable to move, so these ropes also belong to a kind of predicament.
  • the area where the cord is located is also a dangerous area; the narrow space with dense legs of tables and chairs, such as near the dining table or in the densely placed area of the table and chairs in the conference room, may make it difficult for the autonomous mobile device trapped in it to escape, so the table Areas with dense chair legs are hazardous areas.
  • the present application proposes the following solutions.
  • a specific type of danger is determined according to specific sensor parameters, and the coordinates of the detected dangerous position and/or its own position when encountering a dangerous position are obtained, so as to determine the dangerous area in the working area, and These dangerous areas are marked on the map of the work area, and these dangerous areas are set as forbidden areas, so that the autonomous mobile device will no longer enter these forbidden areas, thereby reducing the chance of the autonomous mobile device encountering difficulties in subsequent operations.
  • FIG. 1 is a schematic diagram of an application scenario provided by this application.
  • the autonomous mobile device cleaning robot 101 performs cleaning work indoors.
  • the cleaning robot 101 performs cleaning according to the indoor map (ie, the map of the work area) according to the cleaning task.
  • the sensing signals of each sensor are analyzed in real time to determine whether there is a dangerous area, and the route is planned in real time according to the detected dangerous area to avoid difficulties.
  • the indoor map ie, the map of the work area
  • the sensing signals of each sensor are analyzed in real time to determine whether there is a dangerous area, and the route is planned in real time according to the detected dangerous area to avoid difficulties.
  • FIG. 2 is a flowchart of a method for avoiding a dilemma provided by an embodiment of the present application.
  • the method of this embodiment can be applied to an autonomous mobile device. As shown in FIG. 2, the method of this embodiment may include:
  • the dilemma avoidance method may be performed during the operation and mapping of the autonomous mobile device within the work area.
  • the acquired map of the work area refers to a map created while the autonomous mobile device is running.
  • the state values of all locations are set to initial values at the beginning (usually the same as the state values of the unexplored area), and the autonomous mobile device runs in the work area.
  • the position updates its state value or can update the state value of the coordinates that it travels over a period of time based on the trajectory it travels through.
  • the status value of the unexplored position is preset to 75; the status value of the coordinates corresponding to the reachable and passed positions is set to 0, and the status value of the coordinates corresponding to the position that is blocked by obstacles and cannot be reached is set to 0. Set or update to 100.
  • one way of setting the dangerous area is to define the dangerous area by setting the state value of the coordinate corresponding to the dangerous location, for example, updating the state value of the coordinate corresponding to the identified dangerous location to 90.
  • more detailed status values can also be set to further quantify the type or degree of danger. For example, if the types of danger are divided into five categories, the status values of these five types of dangerous locations can be set to 91, 92, and 93 respectively. , 94, 95, and so on.
  • the autonomous mobile device When the state value of the coordinates of the current position of the autonomous mobile device is 90 indicating the dangerous position or the state values 91 to 95 of the coordinates corresponding to the refined type of danger, the autonomous mobile device is controlled to stop, turn or retreat , so that it does not enter the restricted area.
  • the autonomous mobile device is controlled to stop, turn or retreat, so as not to enter the restricted area.
  • the state value of the coordinates within the restricted area may not be set, that is, the autonomous mobile device only needs to determine that it has entered the coordinate range of the restricted area, but may not determine the state value of the coordinates in the restricted area.
  • the dilemma avoidance method may be performed alone within a work area where the autonomous mobile device has been operating and has been mapped.
  • the acquired map of the work area may be a map that has already been constructed.
  • the constructed map (or called historical map) may be previously constructed by the autonomous mobile device and stored in the autonomous mobile device or in the server.
  • Each location in the constructed map has a state value of clear coordinates, for example, the state value of the unexplored location is 75; the state value of the coordinates corresponding to the reachable and passed locations is 0;
  • the status value of the coordinates corresponding to the position that is blocked by obstacles and cannot be reached is 100.
  • the constructed map may also be a historical map constructed by other autonomous mobile devices in the same working area in the previous running process and stored in the server.
  • the sweeping robot can store the map of the family house that it has built after running in the server, and although the mopping robot itself has not run in the working area, it can directly obtain the historical map of the working area of the family house from the server. .
  • the map of the work area can also be a map edited by the user.
  • the user can obtain the historical map uploaded by the autonomous mobile device to the cloud service in the mobile phone, edit the historical map by adding, modifying, deleting and other operations and save it, and then the autonomous mobile device can download and use the modified history from the server. map.
  • the autonomous mobile device operates in the work area.
  • the autonomous mobile device can load a map of the work area before or during a mission. Corresponding operations will be performed in areas marked as dangerous, including but not limited to: evasive operations such as stopping, steering, etc. and/or deceleration, etc. For example, when the state value of the coordinates of the current position of the autonomous mobile device is 90 indicating the dangerous location or the state values 91 to 95 of the coordinates corresponding to the refined type of danger, the autonomous mobile device is controlled to stop and turn. Or step back so that it does not enter the restricted area.
  • the autonomous mobile device is controlled to stop, turn or retreat. , so that it does not enter the restricted area. Users can also customize the corresponding actions.
  • the map of the work area will be updated, and the original information will be added, deleted or modified. For example, in the position that has been reached and restricted by obstacles, the state value of its coordinates will be updated from the original 0 to 100. ; update the state value of the coordinates from 100 to 90 for locations that used to be normal obstacles but are now detected as predicaments, etc.
  • the autonomous mobile device can still create the work area map in real time during the movement process, and perform corresponding operations, as shown in the above step S201.
  • the work area map can be stored locally on the device or on the cloud server, or can be sent to the user for further operations.
  • Autonomous mobile devices operate in the work area to perform specific tasks, such as cleaning robots performing indoor floor cleaning tasks in the work area.
  • S203 Acquire sensing information collected by at least one sensor of the autonomous mobile device, and the sensing information can be used to obtain the environmental state of the location of the autonomous mobile device when acquiring the sensing information or the same as when the autonomous mobile device acquires the sensing information The state of the environment at the location at the detection distance.
  • the autonomous mobile device can obtain the sensing information of the sensor at all times to monitor the environmental state of the location where the autonomous mobile device obtains the sensing information of the sensor or the detection distance from the location where the autonomous mobile device obtains the sensing information. the state of the environment.
  • the first type is a sensor used to detect the environmental information of the location of the autonomous mobile device when it acquires the sensing information.
  • the sensor information of this type of sensor can directly determine the environmental state of the location of the autonomous mobile device when it acquires the sensory information.
  • collision sensors can be used to detect whether there are obstacles (environmental information), and determine whether there are obstacles (environmental status) where the autonomous mobile device is located; anti-drop sensors can be used to detect changes in ground height (environmental information) , to determine whether there are concave structures on the ground such as steps or raised structures on the ground such as lamp sockets and fan sockets (environmental status) around the location of the autonomous mobile device; the humidity sensor can detect the ambient humidity (environmental information) and determine the location near the autonomous mobile device. Whether the humidity is too high (environmental state); the optical flow sensor can be used to detect changes in the ground material (environmental information), and determine whether the location of the autonomous mobile device has become a carpet, etc. Materials (environment states); etc.
  • the second type of sensor for providing sensing information is a sensor that infers the external environmental state by detecting the working state information of the autonomous mobile device itself.
  • the wheel drop sensor can infer whether the wheel set has left the ground at this time (environmental state) by detecting the compressed state of the wheel set (self-operating state information);
  • the current/power sensor installed on the wheel set drive motor (such as The resistor connected in series in the circuit, if its current value can be detected, it can be used as a current sensor) can be used to detect whether the current/power of the driving motor is too high (its own working status information), and then infer the location of the autonomous mobile device Whether the ground material hinders its travel, or whether there are ropes and other winding wheels (environmental state); by detecting whether the current/power on the drive motor is too low (self-operating state information), it can be inferred whether the autonomous mobile device is held at its location. lift, lift, or slip (ambient state), etc.
  • the third type of sensor for providing sensing information is a sensor for detecting the environmental state at a detection distance from the location where the autonomous mobile device obtained the sensing information.
  • a proximity sensor can non-contactly detect obstacles/dilemmas (environmental information) at a certain distance from it; a proximity sensor placed on the edge of an autonomous mobile device can non-contactly detect the environment at a certain detection distance from the autonomous mobile device with horizontal detection light obstacles/dilemmas (environmental states) in .
  • a temperature sensor or a thermal infrared sensor can be used to detect the ambient temperature (environmental information), and determine whether there is a high temperature (environmental state) at a detection distance from the location where the autonomous mobile device obtains the sensing information.
  • S204 determine whether the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at a detection distance from the location where the autonomous mobile device is acquiring the sensing information is difficult.
  • a single sensing information or a combination of multiple sensing information may correspond to some specific dilemmas at the location of the autonomous mobile device, and the relevant correspondence can be pre-stored in the autonomous mobile device for judging the dilemma.
  • the following sets of correspondences are listed as examples.
  • the anti-drop sensor is usually arranged at the bottom of the autonomous mobile device and downward to detect the change of the distance between the bottom and the ground.
  • an infrared pair tube or TOF time of flight
  • the sensing information output by the anti-drop sensor is usually a continuous and relatively stable value without drastic fluctuations.
  • the anti-drop sensor is running, the sensing information output by the anti-drop sensor will change drastically, which means that the distance between the anti-drop sensor and the ground has a dramatic height change.
  • the position when the sensing information output by the anti-drop sensor changes drastically can be determined as a type of dangerous position.
  • the wheel drop sensor combined with the current sensor of the wheel set can detect the dangerous area where entanglement may occur, such as if the bottom of the curtain is long, there are tassels or ropes dragged to the ground, etc., which may become entangled in the wheel set and/or the autonomous mobile device. Or brush components, at this time, this kind of dilemma can be judged by the wheel drop sensor combined with the sensing information of the current sensor.
  • the wheel drop sensor is connected to the wheel set. When the wheel set touches the ground, the wheel set is compressed, and when the autonomous mobile device is lifted, the wheel set will drop a certain distance under the action of gravity. At this time, the wheel drop sensor (such as a micro sensor) is triggered.
  • the switch or optocoupler thereby sensing that the autonomous mobile device is lifted or the wheel set is suspended.
  • the wheel drop sensor When the wheel drop sensor is triggered and the current of the wheel drive motor decreases (indicating that the resistance of the wheel set to rotate becomes smaller at this time), it can be determined that the machine leaves the ground. You can compare whether the wheel drop sensors of the two wheel sets are triggered. If only one wheel drop sensor is triggered, it means that the machine currently has only one wheel off the ground. hoist. It can also detect the length of time that the wheel down sensor is triggered. If the wheel down sensor is triggered for a short time and then recovers (for example, the time when the wheel down sensor is triggered is less than a certain time threshold), it may be that the autonomous mobile device has been wound for a short time.
  • getting out of trouble or being lifted temporarily can be considered not a difficult situation, but if the wheel-drop sensor is triggered for a long time and does not automatically recover, it can be determined that the current position of the autonomous mobile device is a difficult situation.
  • the wheel-drop sensor is triggered for a long time and does not automatically recover, it can be determined that the current position of the autonomous mobile device is a difficult situation.
  • cleaning robots such as sweeping robots, they are generally equipped with a brush body for collecting dust on the ground.
  • the brush body of the autonomous mobile device is wrapped by the wire, the movement resistance of the brush body will increase, so that the driving motor The output current or output power increases. Therefore, it is possible to assist in determining whether the position of the autonomous mobile device is in a dilemma of entanglement by detecting the current change of the driving motor of the brush body.
  • the wheel drop sensor there is also a situation that can be detected by the wheel drop sensor, such as when the autonomous mobile device is a cleaning robot, when the cleaning robot backs up or rotates, it cannot detect the location of the step due to the lack of an anti-drop sensor behind or on the side of the robot, which may be attached.
  • the autonomous mobile device runs to the step, at least one of its wheels falls under the step. At this time, the wheel is suspended, and the wheel drop sensor will also be triggered.
  • the chassis of the autonomous mobile device may be in direct contact with the ground and wear the chassis. Also a dilemma.
  • a temperature sensor or passive thermal infrared sensor can detect high temperature areas, such as fireplaces.
  • the temperature sensor detects that the temperature value at the detection distance from the position of the autonomous mobile device when acquiring the sensing information exceeds a certain set temperature threshold, it can be considered that there is a heat source within the detection range of the temperature sensor. Excessive temperatures can be detrimental to autonomous mobile device performance, so this situation is also a dilemma.
  • the passive thermal infrared sensor can detect the thermal infrared radiation emitted by the external heat source at a distance from the location where the autonomous mobile device obtains the sensing information. When the detected thermal infrared radiation reaches the set early warning range, it can also indirectly Indicates high temperature distress.
  • the humidity sensor can detect areas with excessive humidity (such as areas near the front or side of the autonomous mobile device). Excessive humidity may short circuit the internal circuits of the autonomous mobile device or reduce the life of accessories. Therefore, the humidity is greater than a certain humidity.
  • a thresholded area such as an area of standing water on a floor, may be identified as a type of dilemma.
  • an optical flow sensor installed at the bottom of an autonomous mobile device and detecting the distance between the bottom and the ground can detect changes in the ground material based on how its light is reflected/scattered.
  • a dual-light source optical flow sensor (which has a laser emitting end and a matching laser receiving end, and an LED infrared emitting end and a matching LED receiving end) is used to detect changes in the ground material.
  • the infrared laser detection line emitted by the laser emitting end of the optical flow sensor will be mirror-reflected on the smooth floor and be reflected into the laser receiving end at the set position; on the carpet, the LED emitting end of the optical flow sensor will be reflected.
  • the emitted infrared rays will be diffusely reflected and enter the LED receiving end.
  • specular reflection will not occur. Therefore, the texture of different ground materials can be identified through the laser and LED of the optical flow sensor, so as to determine the position where the ground material changes.
  • the autonomous mobile device is about to enter the area of the carpet material.
  • the carpet-covered area will be regarded as a dilemma (the dilemma here refers to the damage to the carpet).
  • the ground material change is determined by detecting the current change of the driving motor of the brush body.
  • the autonomous mobile device moves on the carpet, the movement resistance of the main brush and the side brushes on the carpet increases, which will increase the output current of the motor.
  • Mobile devices are in a "carpet" predicament.
  • a threshold such as more than 10 times
  • the location of the autonomous mobile device needs to be determined at this time, and the location or its nearby location is determined as a dangerous location. Since the autonomous mobile device often has a delay in processing the acquired sensor information, when the processed sensor information is obtained, the autonomous mobile device often has advanced a certain distance, so it cannot be judged based on the sensor information at the previous moment. The environmental state of the location at the current moment.
  • the motion parameters output by the dead reckoning sensor of the autonomous mobile device have timestamps
  • Various types of sensors also have their own time stamps when they obtain sensing information, so the motion parameters of the dead reckoning sensor and the sensing information of the sensor can be established based on the same or similar time. The moment of a certain sensing information, the location of the autonomous mobile device, or the environmental information and environmental status at a detection distance from the location of the autonomous mobile device.
  • the way of determining the position corresponding to the predicament may be different according to different sensor types.
  • the position coordinates of the autonomous mobile device that can be detected are the coordinates of the center point of the autonomous mobile device, and the position of the predicament reflected by the sensor information may be some distance away from the center point of the autonomous mobile device.
  • the position of the sensor can be used as the position corresponding to the predicament; for anti-drop sensors and optical flow sensors, although there is a certain detection distance from the predicament, the detection direction is toward the ground.
  • the coordinates of the position corresponding to the dilemma can be considered as the coordinates of the sensor, so the position of the sensor can also be used as the position corresponding to the dilemma.
  • the position of the autonomous mobile device itself can also be used as the position corresponding to the predicament (if the autonomous mobile device is a relatively regular shape such as a cylinder, a square, a D-shaped cylinder, etc., the geometric center of the top view shape is usually used.
  • the position represents its own position.
  • the position of the autonomous mobile device and the position of the collision sensor, anti-drop sensor, optical flow sensor and other sensors arranged on the edge of the autonomous mobile device are only a radius or half a side length at most, and the difference can be ignored. , that is, the position of the autonomous mobile device itself is used to replace the position of the above sensor as the position corresponding to the predicament).
  • the coordinates of the position corresponding to the dilemma need to be based on the coordinates of the sensor and the detection distance of the sensor. get.
  • the detection distance is preset.
  • the proximity sensor sends sensing information, and the position corresponding to the predicament can be approached with The sensor position represents (usually the preset distance is not long, such as 6mm) or the real position of the dilemma is obtained by adding the position vector of the proximity sensor to the detection distance.
  • the TOF used as a proximity sensor is set horizontally to measure the horizontal distance between obstacles in the space and the distance between them, which is also the detection distance of the TOF), if the TOF detects the environment If there is a dilemma at a distance d from it, then d is the detection distance between the TOF and the dilemma. In this step, the positions corresponding to the above dilemmas can all be determined as dangerous positions.
  • the predicament is usually not just a point.
  • the predicament is the entire area bounded by a line along the edge of the sudden drop of the step and extending toward the direction of the step; for a dense area of desks and chairs, the predicament is It is the entire area within the boundary formed by the outermost table and chair legs; for areas with high temperature or high humidity, the edges are blurred, but a reasonable range of dangerous areas can be limited by thresholds. Therefore, when a point of a dilemma is detected, the detected point cannot only be regarded as a dilemma to be avoided.
  • the dangerous area can be defined as a circular area or a square area centered on the dangerous location. Its specific delineation method and size can be set as an empirical value in combination with the properties of the sensor, or set in combination with other sensor states, or determined in combination with current image information. It is also possible to take the detected dangerous position as a certain point on the edge of the dangerous area set by a circular area, a square area, etc., and then extend a certain distance from the center of the autonomous mobile device to the direction of the sensor as the circular area. The center of the circle or the center of the square area to form the set danger zone. Mark the hazardous area on the map of the work area.
  • an anti-drop sensor detects a downward change in height, more likely a step.
  • the danger area can be defined as a circular area, a square area, or the like centered on the position where the downward height change is detected.
  • the relative positional relationship between the machine and the edge of the step can be roughly determined based on the detection signals of all the anti-drop sensors, and then a more accurate range can be calculated. The more accurate the division of hazardous areas, the higher the cleaning rate of the whole house can be made by the machine.
  • the hazardous area can be defined as a circular area centered on the location where the temperature change is detected (heat radiation characteristic of the heat source).
  • the image acquisition device of the autonomous mobile device can also identify the environmental image at the same time, so as to determine the relative positional relationship between the dangerous area and the machine, so as to set the dangerous area.
  • the dilemma avoidance method provided in this embodiment is applied to an autonomous mobile device, and the method includes: acquiring a map of a work area; running the autonomous mobile device in the work area; acquiring sensing information collected by at least one sensor of the autonomous mobile device, and transmitting
  • the sensory information can be used to obtain the environmental state of the location of the autonomous mobile device when acquiring the sensory information or the environmental state at the detection distance from the location of the autonomous mobile device when it acquired the sensory information; according to the sensory information, determine the autonomous movement Whether the environmental state of the location of the device when it acquires the sensing information or the environmental state at the detection distance from the location of the autonomous mobile device when it acquires the sensory information is a predicament; if the location of the autonomous mobile device when it acquires the sensory information is determined If the environmental state or the environmental state at the detection distance from the position of the autonomous mobile device when acquiring the sensing information is a dilemma, the position corresponding to the dilemma is determined as a dangerous location; the dangerous area is marked in the map of the work area according to the dangerous location
  • sensors installed in autonomous mobile devices. According to the sensing information collected by the sensors, it is basically possible to determine the operating state or the environment in which the device collects the sensing information, and then determine whether it is facing potential danger, so as to determine whether the device collects the sensing information. Whether the location of the sensor information is a dangerous location, so as to detect the dangerous area in time and try to avoid the dangerous area during the movement process, reduce or even avoid the situation of being hindered, and improve the working efficiency of the equipment.
  • the device running process of S202 may be parallel to other steps, that is, the device completes steps such as acquiring a map, acquiring sensor information, judging an environmental state, and marking a dangerous area during the running process.
  • S203-S206 may be executed cyclically during the operation of the device, as shown in FIG. 3 .
  • the steps of creating the map and marking the dangerous area can be performed during the operation of the device. As shown in Figure 4.
  • the above-mentioned method of marking the dangerous area in the map of the working area according to the dangerous location may specifically include: acquiring multiple dangerous locations, and marking the geometric shapes formed by the multiple dangerous locations as boundaries on the map of the working area as a hazardous area. For example, use the acquired multiple dangerous positions as points on the boundary of the set geometric shape to form the set dangerous area; or set the acquired multiple dangerous positions on the set center and side length/radius according to the specified method. Within a given geometric shape, a set danger zone is formed. It is also possible to connect multiple obtained hazardous locations, and take the largest area as the hazardous area.
  • the autonomous mobile device can directly re-plan a path according to the determined dangerous area. Avoid this dangerous area. Since there may be deviations in the delineation of the dangerous area by the autonomous mobile device, the scope of the dangerous area can be further revised in this way. For example, autonomous mobile devices avoid this danger zone by steering. In fact, new paths planned by autonomous mobile devices may still not completely leave the actual danger zone here due to deviations. Then, autonomous mobile devices may again detect the same type of danger. In this way, the autonomous mobile device may determine multiple danger locations of the same type within a certain range, and the corrected danger area may be determined as a geometric area bounded by multiple danger locations.
  • a corresponding dangerous area may also be delineated each time a dangerous location is determined, and then, if it is found that there is an overlap between multiple dangerous areas of the same type, the Hazardous area, further define a hazardous area (maximum area or minimum area, etc.).
  • the degree of coincidence between the currently newly determined danger area and the previously determined danger area within a certain period of time is greater than or equal to the preset value, the current newly determined danger area and the previously determined danger area within a certain period of time are combined to form a danger area .
  • the preset value may be, for example, 1/2, or any value not greater than 1 set by the user.
  • the user may also set the scope of the dangerous area. For example, after preliminarily determining the scope of a certain danger area or making further corrections, the determined danger area information may be fed back to the user for confirmation and/or manual correction.
  • Content that can be manipulated by the user can include:
  • the hazard areas in the historical map may also be updated based on the hazard areas in the current map of the work area.
  • the information of the dangerous area can also be updated to the historical map.
  • the way of marking the danger area in the map of the work area according to the danger location may include: determining the danger area according to the danger location; determining the danger category of the danger area; , to mark the hazardous area on the map of the work area.
  • Hazard categories which can be divided by hazard class or by type of hazard. Other criteria can also be used for classification, which is not limited here.
  • the hazard level of the hazardous area can be determined; according to the hazard level, the hazardous area is marked on the map of the work area with the corresponding marking symbol.
  • the determination of the danger level can be determined by the device according to the sensing information, or manually set by the user.
  • the information of the dangerous area can be pushed to the user through the terminal device, and then the user's setting instruction can be received; according to the setting instruction, the danger level of the dangerous area can be determined.
  • High-risk areas can be automatically set by default and marked in red on the map.
  • the junction of carpets and floors, and areas with relatively high humidity it can be set as a low-risk area.
  • the user can be informed by sending prompt information to the user terminal, and the user can delineate its level, or the user can choose whether to set it as a low-risk area, and mark it in yellow on the map.
  • This kind of predicament is set as a passable area, prompting the user to choose and according to the user's choice to determine whether to set it as a restricted area, which can be marked in orange, or determined as a passable area, marked in green, or not marked.
  • the hazard type of the hazard area can be determined; according to the hazard type, the hazard area is marked on the map of the work area with the corresponding marking symbol.
  • the determination of the type of danger can be judged by the autonomous mobile device according to the sensing information.
  • autonomous mobile devices For areas with dense legs of desks and chairs and areas with high humidity, although autonomous mobile devices may be affected to a certain extent, they can eventually escape from these dangerous areas after avoidance, and can be set as a dangerous area that can be escaped.
  • a notification can be sent to inform the user, and the user can choose whether to set it as a dangerous area. If it is determined to be a dangerous area, it can be marked in yellow on the map.
  • the way of marking can be the above-mentioned color marking, or different characters can be used for marking.
  • the above-mentioned high-risk area is marked as “high-risk” or “major dilemma”
  • the above-mentioned low-risk area is marked as “low-risk” or “small dilemma” and so on. This is only an example, and the marking method is not limited.
  • the above-mentioned process of determining the dangerous area can be used as an independent working mode of the autonomous mobile device, such as a "dilemma exploration mode".
  • the task of the autonomous mobile device is to determine the danger zone within the current work area.
  • the above-mentioned determination process of the dangerous area may be performed concurrently with other tasks, such as the task of constructing a map of the work area.
  • the above method further includes: acquiring a work task; planning a path according to the work task and the determined danger area; and moving according to the planned path.
  • the cleaning robot as an example, it can explore the dangerous area and plan the travel path at the same time while performing the cleaning task.
  • the conventional ways to avoid dangerous areas mainly include: rebound avoidance, bow-shaped avoidance, navigation avoidance, and avoidance along the boundary.
  • the avoidance method can be selected according to the current travel mode. For example, if a point-to-point travel (navigation mode from the current position to the target position) is currently in progress, the navigation plan is re-planned, the danger area is bypassed, and then the navigation mode continues to travel to the target point. Referring to Figure 5A.
  • FIG. 6 is a schematic structural diagram of an autonomous mobile device according to an embodiment of the present application.
  • the autonomous mobile device 600 in this embodiment may include: an acquisition module 601 , an operation module 602 , a processing module 603 , and a marking module 604.
  • the acquiring module 601 is used for acquiring the map of the working area.
  • the operation module 602 is used to make the autonomous mobile device operate in the work area.
  • the acquisition module 601 is further configured to acquire sensing information collected by at least one sensor of the autonomous mobile device, and the sensing information is used to obtain the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information, or is used to obtain the sensor information from the autonomous mobile device. The state of the environment when the information is sensed at the location at the detection distance.
  • the processing module 603 is used to judge whether the environmental state of the location where the autonomous mobile device is located when acquiring the sensory information or the environmental state at the detection distance from the location of the autonomous mobile device when acquiring the sensory information is a predicament according to the sensory information; If it is determined that the environmental state of the location where the autonomous mobile device obtains the sensing information or the environmental state at the detection distance from the location of the autonomous mobile device when it obtains the sensing information is a dilemma, the location corresponding to the dilemma is determined as a dangerous location.
  • the marking module 604 is used for marking the dangerous area in the map of the working area according to the dangerous location.
  • the marking module 604 marks the dangerous area in the map of the work area according to the dangerous location, it is specifically used for:
  • Mark areas that include hazardous locations as hazardous areas on a map of the work area are marked areas that include hazardous locations as hazardous areas on a map of the work area.
  • the apparatus 600 further includes: an update module 605, configured to update the dangerous area in the historical map according to the dangerous area in the current map of the working area.
  • the marking module 604 marks the dangerous area in the map of the work area according to the dangerous location, it is specifically used for:
  • the hazardous location determine the hazardous area
  • the hazard category of the hazard area mark the hazard area on the map of the work area with the corresponding marking symbol.
  • the marking module 604 determines the danger category of the danger area, it is specifically used for:
  • the types of hazardous areas include: high-risk areas, low-risk areas;
  • the marking module 604 marks the dangerous area on the map of the working area with the corresponding marking symbol according to the danger category of the dangerous area, it is specifically used for:
  • the category of the dangerous area is a high-risk area, directly mark the dangerous area on the map of the work area with the corresponding mark symbol;
  • the dangerous area is sent to the user terminal, so that the user can determine whether to mark it in the map of the working area.
  • the apparatus 600 further includes a planning module 606 .
  • the obtaining module 601 is also used to obtain work tasks
  • the planning module 606 is configured to perform path planning according to the work task and the determined danger area;
  • the running module 602 is used to move according to the planned path.
  • the acquiring module 601 when acquiring the sensing information collected by at least one sensor of the autonomous mobile device, the acquiring module 601 is specifically used for:
  • the processing module 603 determines whether the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at the detection distance from the location where the autonomous mobile device is acquiring the sensing information is a difficult situation, the specific Used for:
  • the distance is greater than or equal to the preset distance, it is determined that the environmental state of the location of the autonomous mobile device when the distance is acquired is dilemma.
  • the acquiring module 601 when acquiring the sensing information collected by at least one sensor of the autonomous mobile device, the acquiring module 601 is specifically used for:
  • the processing module 603 determines whether the environmental state of the location where the autonomous mobile device is located when acquiring the sensing information or the environmental state at the detection distance from the location where the autonomous mobile device is acquiring the sensing information is a difficult situation, the specific Used for:
  • the environmental state of the location of the autonomous mobile device is dilemma.
  • the apparatus of this embodiment can be used to execute the method of any of the foregoing embodiments, and the implementation principle and technical effect thereof are similar, and are not repeated here.
  • FIG. 7 is a schematic structural diagram of an autonomous mobile device according to an embodiment of the present application.
  • the autonomous mobile device 700 in this embodiment may include: a memory 701 and a processor 702 .
  • the memory 701 is used to store program instructions.
  • the processor 702 is configured to call and execute the program instructions in the memory 701 to execute the method of any of the above embodiments.
  • the autonomous mobile device in this embodiment can be used to execute the method of any of the foregoing embodiments, and the implementation principle and technical effect thereof are similar, which will not be repeated here.
  • the present application also provides a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the method in any of the foregoing embodiments is implemented.
  • the embodiments of the present application further provide a computer program, including program code, when the computer runs the computer program, the program code executes the method described in any of the foregoing embodiments.

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Abstract

一种困境规避方法、自主移动设备(600,700)和存储介质，其中的困境规避方法包括：获取工作区域的地图(S201)；自主移动设备(600,700)在工作区域中运行(S202)；获取自主移动设备(600,700)的至少一个传感器采集到的传感信息，传感信息能够被用于得到自主移动设备(600,700)在获取传感信息时所在位置的环境状态或与自主移动设备(600,700)在获取传感信息时所在位置相距检测距离处的环境状态(S203)；根据传感信息，判断自主移动设备(600,700)在获取传感信息时所在位置的环境状态或与自主移动设备(600,700)在获取传感信息时所在位置相距检测距离处的环境状态是否为困境(S204)；若确定为困境，则将困境对应的位置确定为危险位置(S205)；根据危险位置，在工作区域的地图中标记危险区域(S206)。通过此方法可以减少甚至避免自主移动设备(600,700)被阻碍运行的情况。

Description

困境规避方法、自主移动设备和存储介质
本申请要求于2020年10月30日提交中国专利局、申请号为202011198040.3、申请名称为“困境规避方法、自主移动设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及智能控制技术，尤其涉及一种困境规避方法、自主移动设备和存储介质。
背景技术
随着科技进步，具有不同功能的自主移动设备越来越多地进入了人们的生活，为人们提供更多的便利。
自主移动设备通常会在一个有限空间内的地面上自主移动执行各类任务，该有限空间内的地面可以称为自主移动设备的工作区域。根据自主移动设备的类型不同，其工作区域的环境也不相同。很多自主移动设备的工作区域内环境较为复杂，可能对自主移动设备的运行造成阻碍。
相关技术中，自主移动设备在运行过程中并不能很好地规避这些阻碍，导致运行中断，降低自主移动设备的工作效率，甚至设备损坏。
发明内容
本申请提供一种困境规避方法、自主移动设备和存储介质，由自主移动设备自行识别可能遇到的障碍，并构建危险区域，在运行过程中避开危险区域，减少甚至避免被阻碍的情况，提高设备的工作效率。
第一方面，本申请提供一种困境规避方法，应用于自主移动设备，所述方法包括：
获取工作区域的地图；
所述自主移动设备在所述工作区域中运行；
获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息能够被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；
若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
根据所述危险位置在所述工作区域的地图中标记危险区域。
可选的，所述根据所述危险位置在所述工作区域的地图中标记危险区域，包括：
将包括所述危险位置的区域在所述工作区域的地图中标记为危险区域；和/或，
获取多个彼此临近的危险位置，将包括多个彼此临近的危险位置的区域在所述工作区域的地图中标记为危险区域。
可选的，所述方法还包括：
根据工作区域的当前地图中的危险区域更新历史地图中的危险区域。
可选的，所述根据所述危险位置在所述工作区域的地图中标记危险区域，包括：
根据所述危险位置，确定危险区域；
确定所述危险区域的危险类别；
根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中。
可选的，所述确定所述危险区域的危险类别，包括：
接收用户的设置指令；
根据所述设置指令，确定所述危险区域的危险类别。
可选的，所述危险区域的类型包括：高危险区域、低危险区域；
所述根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中，包括：
若所述危险区域的类别为高危险区域，则直接以对应的标记符号，将所述危险区域标记在所述工作区域的地图中；
若所述危险区域的类别为低危险区域，则将所述危险区域发送给用户终端，以使用户确定是否将其标记在所述工作区域的地图中。
可选的，所述方法还包括：
获取工作任务；
根据所述工作任务、已经确定的危险区域，进行路径规划；
按照规划好的路径移动。
可选的，所述获取所述自主移动设备的至少一个传感器采集到的传感信息，包括：
获取所述自主移动设备中防跌落传感器采集到的距离；
所述根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境，包括：
判断所述距离是否小于预设距离；
若所述距离大于或等于预设距离，则确定所述自主移动设备在获取所述距离时所在位置的环境状态为困境。
可选的，所述获取所述自主移动设备的至少一个传感器采集到的传感信息，包括：
获取所述自主移动设备中轮降传感器被触发的传感信息；
所述根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境，包括：
确定所述自主移动设备的轮降传感器被触发时，自主移动设备所在位置的环境状态为困境。
第二方面，本申请提供一种自主移动设备，包括：
获取模块，用于获取工作区域的地图；
运行模块，用于使所述自主移动设备在所述工作区域中运行；
所述获取模块，还用于获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
处理模块，用于根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
标记模块，用于根据所述危险位置在所述工作区域的地图中标记危险区域。
可选的，所述标记模块在根据所述危险位置在所述工作区域的地图中标记危险区域时，具体用于：
将包括所述危险位置的区域在所述工作区域的地图中标记为危险区域；和/或，
获取多个彼此临近的危险位置，将包括多个彼此临近的危险位置的区域在所述工作区域的地图中标记为危险区域。
可选的，所述设备还包括：更新模块，用于根据工作区域的当前地图中的危险区域更新历史地图中的危险区域。
可选的，所述标记模块在根据所述危险位置在所述工作区域的地图中标记危险区域时，具体用于：
根据所述危险位置，确定危险区域；
确定所述危险区域的危险类别；
根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中。
可选的，所述标记模块在确定所述危险区域的危险类别时，具体用于：
接收用户的设置指令；
根据所述设置指令，确定所述危险区域的危险类别。
可选的，所述危险区域的类型包括：高危险区域、低危险区域；
所述标记模块在根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中时，具体用于：
若所述危险区域的类别为高危险区域，则直接以对应的标记符号，将所述危险区域标记在所述工作区域的地图中；
若所述危险区域的类别为低危险区域，则将所述危险区域发送给用户终端，以使用户确定是否将其标记在所述工作区域的地图中。
可选的，所述获取模块还用于：获取工作任务；
所述处理模块，还用于根据所述工作任务、已经确定的危险区域，进行路径规划；
所述运行模块，用于按照规划好的路径移动。
可选的，所述获取模块在获取所述自主移动设备的至少一个传感器采集到的传感信息时，具体用于：
获取所述自主移动设备中防跌落传感器采集到的距离；
所述处理模块在根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境时，具体用于：
判断所述距离是否小于预设距离；
若所述距离大于或等于预设距离，则确定所述自主移动设备在获取所述距离时所在位置的环境状态为困境。
可选的，所述获取模块在获取所述自主移动设备的至少一个传感器采集到的传感信息时，具体用于：
获取所述自主移动设备中轮降传感器被触发的传感信息；
所述处理模块在根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境时，具体用于：
确定所述自主移动设备的轮降传感器被触发时，自主移动设备所在位置的环境状态为困境。
第三方面，本申请提供一种自主移动设备，包括：存储器，用于存储程序指令；处理器，用于调用并执行所述存储器中的程序指令，执行第一方面所述的方法。
第四方面，本申请提供一种计算机可读存储介质，所述存储介质存储有计算机程序，所述计算机程序被处理器执行时，实现第一方面所述的方法。
第五方面，本申请提供一种计算机程序，包括程序代码，当计算机运行所述计算机程序时，所述程序代码执行如第一方面所述的方法。
第六方面，本申请提供一种程序产品，所述程序产品包括计算机程序，所述计算机程序存储在可读存储介质中，自主移动设备的处理器可以从所述可读存储介质读取所述计算机程序，所述处理器执行所述计算机程序使得自主移动设备实施如第一方面所述的方法。
本申请提供了一种困境规避方法、自主移动设备和存储介质。该困境规避方法，应用于自主移动设备，所述方法包括：获取工作区域的地图；所述自主移动设备在所述工作区域中运行；获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息能够被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；根据所述危险位置在所述工作区域的地图中标记危险区域。自主移动设备中设置有多种类型的传感器，根据传感器采集到的传感信息，基本可以确定设备采集到传感信息时的运行状态或所处环境，进而确定是否面临潜在危险，从而确定设备采集到传感信息时的所在位置是否属于危险位置，以便及时发现危险区域并在移动过程中尽量对危险区域进行躲避绕行，减少甚至避免被阻碍运行的情况，提高设备的工作效率。
附图说明
为了更清楚地说明本申请或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本申请提供的一种应用场景的示意图；
图2为本申请一实施例提供的一种困境规避方法的流程图；
图3为本申请一实施例提供的另一种困境规避方法的流程图；
图4为本申请一实施例提供的另一种困境规避方法的流程图；
图5A为本申请一实施例提供的一种导航示意图；
图5B为本申请一实施例提供的一种导航示意图；
图6为本申请一实施例提供的一种自主移动设备的结构示意图；
图7为本申请一实施例提供的一种自主移动设备的结构示意图。
具体实施方式
为使本申请的目的、技术方案和优点更加清楚，下面将结合本申请中的附图，对本申请中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
自主移动设备是指在设定区域内自主执行预设任务的智能设备。目前，自主移动设备通常包括但不限于清洁机器人(例如智能扫地机、智能擦地机、擦窗机器人等)、陪伴型移动机器人(例如智能电子宠物、保姆机器人等)、服务型移动机器人(例如酒店、旅馆、会晤场所的接待机器人)、工业巡检智能设备(例如电力巡检机器人、智能叉车等)、安防机器人(例如家用或商用智能警卫机器人)等。
自主移动设备通常会在一个有限空间内的地面上自主移动执行各类任务，比如清洁机器人、陪伴型移动机器人通常在室内地面上运行，服务型移动机器人通常在旅馆、会场等空间内的地面上运行。这个有限空间内的地面可以称为自主移动设备的工作区域。
自主移动设备运行过程中，可能遭遇环境中的诸多“困境”。在本申请中，困境是指工作区域内，阻碍自主移动设备在地面上移动使其无法或很难脱离该区域的各类障碍物，或凸起、凹陷等各类结构，或可能对自主移动设备本身或地面造成损伤、或可能对用户带来危险的各类障碍物、环境情况等。由于工作区域内的困境通常占有一定的范围，比如灯座占有的范围就是灯座在地面占有的面积，桌椅密集区域占有的范围可以等同为其最外围桌椅腿所围成的区域，因此该困境所占的范围构成了最小的危险区域。因此本申请中，将自主移动设备遇到困境处的位置称为危险位置；将困境所在的区域对应的地面区域称为危险区域。例如，台阶或楼梯等有高度落差的物体或结构，可能造成自主移动设备的跌落损坏，则台阶或楼梯是一类困境，而台阶或楼梯的位置为危险位置或危险区域；灯座、风扇座等高出地面的凸起结构，可能使自主移动设备被垫起使轮子空转，则灯座、风扇座是一类困境，而灯座、风扇座的位置为危险位置或危险区域；移动门的导轨等凹凸不平且窄小的缝隙处，可能导致自主移动设备的轮子被卡住，因此也属于一类困境；特别光滑的地面 或带有积水的地面可能使自主移动设备的轮子打滑，使其码盘计算的里程不准，因此也属于一类困境；落地窗帘等悬挂物拖拉在地面的绳线等，可能缠住自主移动设备的轮子，使其无法运动，因此这些线绳也属于一类困境，而线绳所在的区域也是危险区域；桌椅腿密集的狭小空间，比如餐桌附近或会议室的桌椅密集摆放区域等，可能使陷于其中的自主移动设备很难脱离，因此桌椅腿密集区域属于危险区域。当然为了计算简便，也可以在最小的危险区域基础上适当扩大，使其形状较简单、易于计算，同时使自主移动设备不容易在同一位置附近被同一困境多次阻挡。由于困境对自主移动设备造成的影响类型、影响程度有所不同，可以相应地对危险区域的危险类型、危险程度等进行划分。
由于同一工作区域的大小、形状、布局通常比较固定，其中的物品摆放也不常变化，同一工作区域内引起困境的障碍物或结构的位置、尺寸、形状、危险类型都变化不大，导致自主移动设备在同一工作区域内多次运行时，经常在同一位置附近被同一困境多次反复困住。
基于现有技术的上述问题，本申请提出以下解决方案。在自主移动设备运行过程中，依据特定的传感器参数确定特定的危险类型，并获取检测到的危险位置的坐标和/或遇到危险位置时自身的位置，从而确定工作区域内的危险区域，并将这些危险区域标记在工作区域的地图中，将这些危险区域设置为禁区，使自主移动设备不再进入这些禁区，从而在后续运行中降低自主移动设备遇到困境的几率。
图1为本申请提供的一种应用场景的示意图。如图1所示，自主移动设备清洁机器人101在室内执行清洁工作。清洁机器人101根据清洁任务，按照室内地图(即工作区域的地图)进行清洁。在移动过程中，实时对各个传感器的传感信号进行分析，判断是否存在危险区域，并根据检测到的危险区域对路线进行实时规划，以躲避困境。具体的实现方式可以参考下述各实施例。
图2为本申请一实施例提供的一种困境规避方法的流程图。本实施例的方法可应用于自主移动设备。如图2所示，本实施例的方法可以包括：
S201、获取工作区域的地图。
在一些实施例中，困境规避方法可能在自主移动设备在工作区域内运行并建图的过程中执行。此时，获取到的工作区域的地图是指自主移动设备一边运行一边创建的地图。在地图创建的过程中，起始时所有位置的状态值均设定为初始值(通常与未探索区域的状态值一致)，自主移动设备在工作区域中运行，每到达一个位置，则对该位置更新其状态值或者可以根据其在一段时间内经过的轨迹更新这段轨迹上经过的坐标的状态值。例如，对于未探索的位置的状态值先预设为75；将可到达的和已经通过的位置对应的坐标的状态值设置为0，将障碍物阻挡而无法到达的位置对应的坐标的状态值设置或更新为100。
作为一个实施例，设置危险区域的一种方式是通过设置危险位置对应的坐标的状态值来限定危险区域，比如将识别出的危险位置对应的坐标的状态值更新为90。针对危险位置，还可以设置更细化的状态值以进一步量化危险的种类或程度，比如将危险类型分为5类，则可以将这五类危险位置的状态值分别设置为91、92、93、94、95，以此类推。当自主移动设备的当前时刻所在位置的坐标的状态值为上述表示危险位置的90或上述与细化的危险类型对应的坐标的状态值91至95处，则控制自主移动设备停止、转向或后退，使其不进入该禁区范围。
作为一个实施例，设置危险区域的另一种方式，还可以在工作区域的地图上划定一个区域作为禁区，在自主移动设备移动过程中判断其当前时刻所在位置是否在该禁区之内；如果检测到自主移动设备接近或到达禁区边界，则控制自主移动设备停止、转向或后退，使其不进入该禁区范围。该实施例中，可以不用对禁区范围内的坐标的状态值进行设定，也就是说，自主移动设备只要判断进入了禁区的坐标范围，而可以不判断禁区内的坐标的状态值。
在另一些实施例中，在自主移动设备曾经运行过且已建立地图的工作区域内，困境规避方法可以单独执行。此时，获取到的工作区域的地图可以为已经构建好的地图。构建好的地图(或称为历史地图)可以是自主移动设备在之前构建好并存储在自主移动设备中或服务器中的。构建好的地图中的各个位置均有明确的坐标的状态值，例如，对于未探索的位置的状态值为75；对于可到达的和已经通过的位置对应的坐标的状态值为0；对于因为障碍物阻挡而无法到达的位置对应的坐标的状态值为100。也可以使历史地图中的坐标的状态值与新创建的地图的坐标的状态值不同，比如在历史地图中对未探索的位置的状态值为75；对于可到达的和已经通过的位置对应的坐标的状态值为15；对于因为障碍物阻挡而无法到达的位置对应的坐标的状态值为25，以显示与新创建地图的区别，本申请不对新创建地图以及历史地图中状态值的设定规则做限制。构建好的地图也可以是其它自主移动设备在同一个工作区域在之前的运行过程中构建好并存储在服务器中的历史地图。例如，在某个家庭中同时有一扫地机器人和一拖地机器人，因都是对同一家庭住房内的地面进行清洁，两个设备的工作区域相同。扫地机器人可以将其运行后已经构建好的家庭住房的地图存储在服务器中，而拖地机器人虽然自身并未在该工作区域运行过，但可以直接从服务器中获取该家庭住房工作区域的历史地图。
在另一些实施例中，工作区域的地图也可以为用户编辑后的地图。例如，用户可以在手机中获取自主移动设备上传到云服务中的历史地图，通过增加、修改、删除等操作对历史地图进行编辑后保存，再由自主移动设备从服务器中下载使用修改后的历史地图。
S202、自主移动设备在工作区域中运行。
自主移动设备可在任务开始前或者执行任务过程中加载工作区域地图。在标识为危险的区域会进行相应的操作，包括但并不限于如：停止、转向等规避操作和/或减速等。比如，当自主移动设备的当前时刻所在位置的坐标的状态值为上述表示危险位置的90或上述与细化的危险类型对应的坐标的状态值91至95时，则控制自主移动设备停止、转向或后退，使其不进入该禁区范围。或者，在对工作区域的地图上划定一个区域作为禁区的实施例中，若在自主移动设备移动过程中判断其当前时刻所在位置接近或到达禁区边界，则控制自主移动设备停止、转向或后退，使其不进入该禁区范围。用户也可以自定义相应的动作。在执行任务过程中会对工作区域地图进行更新，对原有信息进行增加、删除或者修改，比如在曾经达到过而限制有障碍物的位置，将其坐标的状态值由原来的0更新为100；对曾经是普通障碍物而现在被检测是困境的位置，将其坐标的状态值由100更新为90，等等。
如果工作区域地图加载失败，自主移动设备仍然可以在运动过程中实时创建工作区域地图，并进行相应的操作，如上述步骤S201。
在执行任务过程中或者执行任务完成后，工作区域地图可以存储在设备本地或者云端服务器上，也可以发送给用户供进一步操作。
自主移动设备在工作区域中运行执行特定任务，比如清洁机器人在工作区域中进行室内地面的清洁任务。
S203、获取自主移动设备的至少一个传感器采集到的传感信息，传感信息能够被用于得到自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态。
在运行过程中，自主移动设备可以时刻获取传感器的传感信息，以监测自主移动设备获取传感器的传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态。
自主移动设备中通常包括三类用于提供传感信息的传感器。第一类为用于检测自主移动设备在获取传感信息时所在位置的环境信息的传感器，通过这类传感器的传感信息可以直接判断自主移动设备在获取传感信息时所在位置的环境状态。例如，碰撞传感器可以用于检测是否存在障碍物(环境信息)，判断自主移动设备所在位置是否有阻挡其行进的障碍物(环境状态)；防跌落传感器可以用于检测地面高度变化(环境信息)，判断自主移动设备所在位置周边是否有台阶等地面凹下结构或灯座、风扇座等地面凸起结构(环境状态)；湿度传感器可以检测环境湿度(环境信息)，判断自主移动设备所在位置附近是否湿度过高(环境状态)；光流传感器可以用于检测地面材质变化(环境信息)，判断自主移动设备所在位置是否变为地毯等不适合擦地机或扫拖一体机的擦地模式的材质(环境状态)；等等。
第二类用于提供传感信息的传感器为通过检测自主移动设备自身工作状态信息从而推断外部的环境状态的传感器。例如，轮降传感器可以通过检测轮组的被压缩的状态(自身工作状态信息)，推断轮组此时是否已离开地面(环境状态)；安装在轮组驱动马达上的电流/功率传感器(比如串联在电路中的电阻，如果能检测其电流值，即可将其作为电流传感器使用)可以用于检测驱动马达的电流/功率是否过高(自身工作状态信息)，进而推断自主移动设备所在位置地面材质是否阻碍其行进、或者是否有线绳等缠绕轮组(环境状态)；通过检测驱动马达上的电流/功率是否过低(自身工作状态信息)可以推断自主移动设备在其所在位置是否被抱起、抬起或发生打滑(环境状态)，等等。
第三类用于提供传感信息的传感器为用于检测与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态的传感器，通过这类传感器的传感信息可以判断与自主移动设备相距一定距离位置处而非自主移动设备自身所在位置处的环境状态。例如，接近传感器可以非接触检测与其相距一定距离的障碍物/困境(环境信息)；设置在自主移动设备边缘的接近传感器可以以水平探测光线非接触地检测与自主移动设备相距一定检测距离的环境中的障碍物/困境(环境状态)。比如，温度传感器或热红外传感器可以用于检测环境温度(环境信息)，判断与自主移动设备在获取所述传感信息时所在位置相距检测距离处是否存在高温(环境状态)。
S204、根据传感信息，判断自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态是否为困境。
单个的传感信息或多个传感信息的组合可能对应着自主移动设备所在位置的某些特定的困境，相关的对应关系可以预先存储在自主移动设备中，用于判断困境。下面作为例子列举几组对应关系。
例如，防跌落传感器通常设置在自主移动设备底部并向下设置，用于检测其底部与地面之间的距离变化，比如可以采用红外对管或TOF(time of flight)作为防跌落传感器。当自主移动设备在平坦地面上行进时，防跌落传感器输出的传感信息通常是持续的相对稳定的值，没有剧烈的起伏变化，而当自主移动设备在有凹凸突变的地面(比如前方有楼梯等剧烈凹陷或灯座等明显凸起结构)运行时，防跌落传感器输出的传感信息会有剧烈变化，代表防跌落传感器与地面距离有剧烈的高度变化。对于自主移动设备而言，如果继续向前运行，则可能会被卡住或发生轮组跌落，使其运行受阻，甚至会使自主移动设备受到损伤，这类位置就属于困境。因此，防跌落传感器输出的传感信息发生剧烈变化时的位置就可以被确定为一类危险位置。
再例如，轮降传感器结合轮组的电流传感器可以检测到可能发生缠绕的危险区域，例如如果窗帘底部较长、有拖拉到地面的穗子或线绳等则可能缠绕自主移动设备的轮组和/或刷组件，此时可以通过轮降传感器结合电流传感器的传感信息判断这类困境。轮降传感器与轮组连接，当轮组接触地面时，轮组被压缩，而当自主移动设备被抬起时，轮组在重力作用下会落下一定距离，此时触发轮降传感器(比如微动开关或光耦)，由此感知自主移动设备被抬起或轮组悬空。当轮降传感器被触发，并且轮组驱动马达的电流减小(说明此时轮组旋转的阻力变小)时，可以判断确定机器离开地面。可以比较两个轮组的轮降传感器是否均被触发，如果只有一个轮降传感器被触发，说明机器当前只有一个轮子离开地面，这种情况可能是其中一个轮子被线绳等缠绕而使其被吊起。还可以检测轮降传感器被触发的时长，若轮降传感器被触发的时间较短即恢复(比如轮降传感器被触发的时间小于某个时间阈值)，则可能是自主移动设备被缠绕很短时间即脱困或者暂时被抬起，可以认为并非困境，但若轮降传感器被触发的时间较长而未自动恢复，可以确定自主移动设备当前位置为困境。或者，对于清洁机器人，例如扫地机器人，一般会配备用于将地面灰尘归拢的刷体，当自主移动设备的刷体被线绳缠绕时，会导致刷体的运动阻力增大，从而使驱动马达的输出电流或输出功率增大。因此可以通过检测刷体的驱动马达的电流变化来辅助确定自主移动设备所在位置是否存在发生缠绕的困境。还有一种情况可以由轮降传感器检测，比如当自主移动设备是清洁机器人，在清洁机器人后退或旋转时，由于其后方或侧后方通常缺少防跌落传感器而无法检测该位置附件的台阶，可能会导致自主移动设备运行到台阶处时，其至少一个轮子跌落到台阶下，此时轮子悬空，也会触发轮降传感器，此时可能使自主移动设备的底盘与地面直接接触而磨损底盘，因此这也是一类困境。
再例如，温度传感器或被动热红外传感器可以检测到高温区域，例如壁炉等。当温度传感器检测到与自主移动设备在获取传感信息时所在位置相距检测距离处的温度值超出某一设定温度阈值时，可以认为温度传感器的检测范围内有热源。温度过高可能会对自主移动设备性能造成损害，因此这种情况也是一种困境。被动热红外传感器可以检测到与自主移动设备在获取传感信息时所在位置相距检测距离处的外部热源发出的热红外辐射，当检测到的热红外辐射达到设定的预警范围时，同样可以间接指示高温困境。
再例如，湿度传感器可以检测到湿度过大的区域(比如临近自主移动设备前部或侧部区域)，湿度过大可能会对自主移动设备内部电路短路或降低配件寿命，因此，湿度大于一定湿度阈值的区域(比如地板上的积水区域)可被确定为一类困境。
再例如，安装在自主移动设备底部且检测其底部与地面距离的光流传感器可以根据其 光线被反射/散射的情况检测地面材质变化。例如，采用双光源光流传感器(其具有激光发射端和与之匹配的激光接收端，以及具有LED红外发射端以及与之匹配的LED接收端)检测地面材质变化。在地板上，光流传感器的激光发射端发出的红外激光探测线会在光滑的地板发生镜面反射而被反射进入设定好位置的激光接收端；而在地毯上，光流传感器的LED发射端发出的红外线会发生漫反射而进入其LED接收端，此时由于地毯质地松软，不会发生镜面反射。因此可以通过光流传感器的激光和LED分别识别不同地面材质的纹理，从而确定地面材质发生变化的位置。通过其输出信号的变化，确定自主移动设备即将进入地毯材质的区域。对于擦地机或扫拖一体机的擦地模式，往往不希望其在地毯区域运行，可能对地毯造成损伤，此时地毯覆盖区域将被视为困境(此处的困境是指对地毯的损伤，但不一定对自主移动设备本身有损伤或不利)。或者，通过检测刷体的驱动马达的电流变化确定地面材质变化。当自主移动设备运动到地毯上之后，主刷和边刷在地毯上的运动阻力增大，会使马达的输出电流增大，因此可以通过刷体马达的输出功率或输出电流的突变来确定自主移动设备所在位置为“地毯”困境。
再例如，利用在一段较短的时间范围内(比如5分钟)，设置在自主移动设备周边(特别是其前部)的碰撞传感器与外部障碍物发生碰撞的次数是否达到阈值(比如超过10次)判断自主移动设备是否遇到了桌椅密集区域的困境。当然也可以基于碰撞传感器在一段时间内发生碰撞的频率来确定此类困境，由此可以大致确定自主移动设备进入了桌椅密集区域或周围有比较多障碍物的狭小空间。
S205、若确定自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态为困境，则将困境对应的位置确定为危险位置。
若根据传感信息判断自主移动设备在获取传感信息时所在位置的环境状态为困境，则在该步骤需要确定此时自主移动设备的位置，将该位置或其附近位置确定为危险位置。由于自主移动设备在处理所获取的传感信息时，往往有延时，所以在得到处理后的传感信息时，自主移动设备往往已经前进了一段距离，因此不能以之前时刻的传感信息判断当前时刻所在位置的环境状态。但是由于自主移动设备的航位推算传感器输出的运动参数(自主移动设备中的码盘用于计算位移、其加速度计用于计算加速度、陀螺仪用于计算角速度和角加速度)都有时间戳，而各类传感器在得到传感信息时也具有各自的时间戳，因此可以基于相同或近似的时间对航位推算传感器的运动参数以及传感器的传感信息建立对应关系，从而算出自主移动设备在获取某个传感信息的时刻、自主移动设备所在位置或与自主移动设备所在位置相距检测距离处的环境信息和环境状态。
其中，困境对应的位置的确定方式，根据不同传感器类型可以有所不同。
一般自主移动设备可以检测到的自身的位置坐标是自主移动设备中心点所在位置的坐标，而传感器信息反映的困境的位置距自主移动设备中心点可能还有一段距离。
对于碰撞传感器等通过与困境的直接接触进行检测的传感器，可以以传感器的位置作为困境对应的位置；对于防跌落传感器、光流传感器这类虽然与困境有一定检测距离，但检测方向朝向地面的传感器，困境对应的位置的坐标可以认为是传感器的坐标，因此也可以以传感器的位置作为困境对应的位置。无论对于上述哪种传感器，也可以以自主移动设备自身的位置作为困境对应的位置(若自主移动设备是圆柱体、正方形、D字形柱体等较 规则的形状，通常以其俯视图形状的几何中心位置代表其自身位置，此时自主移动设备自身位置与设置在自主移动设备边缘的碰撞传感器、防跌落传感器、光流传感器等传感器的位置最多仅差一个半径或半个边长，该差别可忽略，即以自主移动设备自身位置代替上述传感器的位置作为困境对应的位置)。
另外，对于检测方向与地面平行且被检测的困境与自主移动设备有一定检测距离的传感器，例如接近传感器或激光雷达(LIDAR)，困境对应的位置的坐标需要根据传感器的坐标和传感器的检测距离得到。对于红外对管型接近传感器，该检测距离是预设的，当困境与接近传感器的距离在该预设的检测距离内时，接近传感器发出传感信息，此时的困境对应的位置可以以接近传感器位置代表(通常预设距离不长，比如6mm)或以接近传感器的位置矢量加该检测距离得到困境的真实位置。对于TOF型接近传感器(TOF是一类激光雷达，水平设置用作接近传感器的TOF用于测量空间内障碍物与其之间的水平距离，该距离也就是TOF的检测距离)，若TOF检测到环境中距其距离d处有困境，则d就是TOF与该困境的检测距离。在该步骤中，上述困境对应的位置都可以确定为危险位置。
S206、根据危险位置，在工作区域的地图中标记危险区域。
在工作区域内，困境通常不会只是一个点，比如对于台阶而言，其困境是由沿台阶突降边缘的一条线为边界、朝向台阶方向延伸的整个区域；对于桌椅密集区域，其困境是最外围桌椅腿练成的边界之内的整个区域；对于高温或高湿度区域，其边缘较为模糊，但可以以阈值限定一个合理的危险区域范围。因此，当检测到困境的一点，不能仅将该被检测到的点作为规避的困境。为避免自主移动设备进入当前危险区域的其它未在本次被探测到的位置，最好是将危险位置对应的整个危险区域在地图中进行标记，或者基于被检测到的危险位置进行一定扩展，人为设定一个危险区域，提高自主移动设备避开困境的几率。
设定危险区域的方法有很多，比如，可以将危险区域划定为以危险位置为中心的圆形区域、方形区域等。其具体的划定方式及大小可以结合传感器的性质设定为经验值，或结合其它传感器状态进行设定，或结合当前图像信息确定。也可以以被检测到的危险位置作为圆形区域、方形区域等设定的危险区域的边缘上的某个点，再沿自主移动设备的中心到传感器的方向延伸一定距离作为该圆形区域的圆心或该方形区域的中心，以此形成设定的危险区域。将该危险区域标记在工作区域的地图中。
例如，防跌落传感器检测到向下的高度变化，更大概率是台阶。可以将危险区域划定为以检测到向下的高度变化的位置为中心的圆形区域、方形区域等。在有两个及以上的防跌落传感器时，可以根据全部防跌落传感器的检测信号，大致判定机器与台阶边缘的相对位置关系，进而推算出更为准确的范围。危险区域划分越准确，即可使得机器对整屋的清洁率更高。
再例如，温度传感器检测到温度变化，更大概率是壁炉或者其它取暖设备。可以将危险区域划定为以检测到温度变化的位置为中心的圆形区域(热源的热量辐射特点)。
或者，还可以同时通过自主移动设备的图像采集装置对环境图像进行识别，以确定危险区域与机器的相对位置关系，从而设定危险区域。
本实施例提供的困境规避方法，应用于自主移动设备，该方法包括：获取工作区域的地图；自主移动设备在工作区域中运行；获取自主移动设备的至少一个传感器采集到的传感信息，传感信息能够被用于得到自主移动设备在获取传感信息时所在位置的环境状态或 与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态；根据传感信息，判断自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态为困境，则将困境对应的位置确定为危险位置；根据危险位置在工作区域的地图中标记危险区域。自主移动设备中设置有多种类型的传感器，根据传感器采集到的传感信息，基本可以确定设备采集到传感信息时的运行状态或所处环境，进而确定是否面临潜在危险，从而确定设备采集到传感信息时的所在位置是否属于危险位置，以便及时发现危险区域并在移动过程中尽量对危险区域进行躲避绕行，减少甚至避免被阻碍运行的情况，提高设备的工作效率。
上述的图2对应的实施例中的步骤顺序仅作为一种示例。实际上，S202的设备运行的过程与其它步骤可能是并行的，即设备在运行过程中完成获取地图、获取传感器信息、判断环境状态、标记危险区域等步骤。
另外，S203-S206在设备运行过程中可能是循环执行的，如图3所示。
在另一种实施例中，若目标区域的地图为新创建的地图，则可以在设备运行过程中，进行地图的创建和危险区域标记的步骤。如图4所示。
在一些实施例中，上述的根据危险位置在工作区域的地图中标记危险区域的方式，具体可以包括：获取多个危险位置，将多个危险位置为边界构成的几何形状标记在工作区域的地图中作为危险区域。比如，将获取的多个危险位置作为设定几何形状的边界上的点，形成设定的危险区域；或按规定的设置中心及边长/半径的方式将获取的多个危险位置设置在设定的几何形状内，形成设定的危险区域。也可以将获取的多个危险位置连接，取其中最大的区域作为危险区域。
在实际的情景中，自主移动设备在执行本申请的方法确定某一危险区域后，可以直接根据确定的此危险区域重新规划路径。对此危险区域进行避让。由于自主移动设备对此危险区域的划定可能存在偏差，故可以采用此种方式对此危险区域的范围进行进一步的修正。例如，自主移动设备通过转向避开此危险区域。实际上，由于偏差，自主移动设备规划的新路径可能仍无法彻底离开此处实际的危险区域。那么，自主移动设备可能再次检测到同类型的危险。如此，自主移动设备可能在某一范围内确定多个同类型的危险位置，修正后的危险区域则可以确定为多个危险位置为边界构成的几何区域。
在另一些实施例中，也可以在每确定一个危险位置时即划定一个对应的危险区域，而后，若发现多个同类型的危险区域之间存在重叠的部分，则可以根据多同类型的危险区域，进一步确定一个危险区域(最大区域或最小区域等)。
例如，若当前最新确定的危险区域与之前一定时长内确定的危险区域的重合度大于或等于预设值，则将当前最新确定的危险区域与之前一定时长内确定的危险区域合并形成一个危险区域。其中，预设值比如可以为1/2，或用户自行设定的任何不大于1的值。
在另一些实施例中，还可以由用户对危险区域的范围进行设定。例如，在初步确定某个危险区域范围或进行进一步修正后，可以将确定的危险区域信息反馈给用户进行确认和/或手动修正。
可供用户操作的内容可以包括：
1、对当前危险区域范围准确度进行确认。若用户确认准确度超过95％(或其它数值)，则短期内不再对此区域进行二次探索；若用户确认准确度较低，则在后续清洁过程中继续对此区域进行探索修正，直至准确度达到用户要求。
2、对当前危险区域范围标定时间进行确认。若用户确认当前危险区域长期存在，则在确定好后，短期内不再对此区域进行二次探索；若用户确认当前危险区域为暂时存在，则在超过设定期限后删除此危险区域，并重新进行探索修正。
3、对当前区域是否为危险区域进行确认。若用户确认为危险区域，则保留标记；否则，删除标记。
在一些实施例中，还可以根据工作区域的当前地图中的危险区域更新历史地图中的危险区域。
对应于上述的获取已经构建好的工作区域的地图，在对地图中的危险区域进行确定后，还可以将危险区域的信息更新到历史地图中。或者，还可以直接将确定了危险区域的当前地图作为工作区域的地图存储起来。
在一些实施例中，根据危险位置在工作区域的地图中标记危险区域的方式可以包括：根据危险位置，确定危险区域；确定危险区域的危险类别；根据危险区域的危险类别，以对应的标记符号，将危险区域标记在工作区域的地图中。
危险类别，可以按危险性等级进行划分，或者按照危险的类型进行划分。也可以以其它标准进行分类，这里不做限定。
以危险等级分类为例，具体的，可以确定危险区域的危险等级；根据危险等级，以对应的标记符号，在工作区域的地图中，标记危险区域。
危险等级的确定，可以由设备根据传感信息判断，或者由用户手动设置。由用户手动设置时，可以将危险区域的信息通过终端设备推送给用户，然后接收用户的设置指令；根据设置指令，确定危险区域的危险等级。
例如，对于台阶、落地窗帘、热源等区域，其导致自主移动设备被困的可能性较大，可以将其设定为高危险区域。对于高危险区域可以默认自动设置，并在地图上以红色标记。
对于地毯、地毯与地板交界处、湿度比较大的区域，则可以设置为低危险区域。对于低危险区域可以通过向用户终端发送提示信息的方式告知用户，由用户对其等级进行划定，或由用户选择是否设置为低危险区域，在地图上以黄色进行标记。
对于电线密集区域、桌椅腿密集区域，由于电线是可移动障碍物，而桌椅板凳的下面有时又需要清洁，且桌椅由于经常搬动使其范围每次可能有所调整而不唯一固定，可以将这类困境设置为可选通行区域，提示用户选择并根据用户的选择确定是否设为禁区，可以以橙色标识，或确定为可通行区域，以绿色标识，或不进行标识。
以危险类型分类为例，具体的，可以确定危险区域的危险类型；根据危险类型，以对应的标记符号，在工作区域的地图中，标记危险区域。
危险类型的确定，可以由自主移动设备根据传感信息进行判断。
例如，对于台阶、落地窗帘等区域，一旦自主移动设备被困，几乎无法主动逃离，可以将其设定为无法逃离的危险区域。对于无法逃离的危险区域可以默认自动设置，并在地图上以红色标记。
对于桌椅腿密集区域、湿度比较大的区域，尽管自主移动设备可能受到一定影响，但 经过避让，最终是可以逃离这些危险区域的，可以将其设定为可以逃离的危险区域。对于可以逃离的危险区域，可以发送通知告知用户，由用户选择是否设置为危险区域，若确定设置为危险区域，则可以在地图上以黄色进行标记。
标记的方式，可以采用上述的颜色标记，也可以不同的文字进行标识。例如，将上述的高危险区域标记为“高危险”或“大困境”，将上述的低危险区域标记为“低危险”或“小困境”等。此处仅为举例，并不对标记方式做限定。
在一个实施例中，上述的危险区域的确定过程，可以作为自主移动设备的一种独立的工作模式，例如“困境探索模式”。在此模式下，自主移动设备的任务即为确定当前工作区域内的危险区域。
在另一些实施例中，上述的危险区域的确定过程可以与其他任务同时进行，例如构建工作区域地图的任务等。上述的方法还包括：获取工作任务；根据工作任务、已经确定的危险区域，进行路径规划；按照规划好的路径移动。
以清洁机器人为例，可以在执行清洁任务的同时，对危险区域进行探索，并同时规划行进路径。
常规的对危险区域进行避让的方式主要有：回弹避让、弓字形避让、导航避让和沿边界避让等。
具体可以根据当前行进模式选择避让方式。例如，当前正在进行点对点行进(由当前位置到目标位置的导航模式)，则重新进行导航规划，绕过危险区域，然后继续以导航形式向目标点行进。参考图5A。
再例如，当前正在进行弓字形覆盖模式，则以弓字形形式进行避让，然后继续进行弓字形覆盖模式。参考图5B。
图6为本申请一实施例提供的一种自主移动设备的结构示意图，如图6所示，本实施例的自主移动设备600可以包括：获取模块601、运行模块602、处理模块603、标记模块604。
获取模块601，用于获取工作区域的地图。
运行模块602，用于使自主移动设备在工作区域中运行。
获取模块601，还用于获取自主移动设备的至少一个传感器采集到的传感信息，传感信息被用于得到自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态。
处理模块603，用于根据传感信息，判断自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态为困境，则将困境对应的位置确定为危险位置。
标记模块604，用于根据危险位置在工作区域的地图中标记危险区域。
可选的，标记模块604在根据危险位置在工作区域的地图中标记危险区域时，具体用于：
将包括危险位置的区域在工作区域的地图中标记为危险区域；和/或，
获取多个彼此临近的危险位置，将包括多个彼此临近的危险位置的区域在工作区域的 地图中标记为危险区域。
可选的，装置600还包括：更新模块605，用于根据工作区域的当前地图中的危险区域更新历史地图中的危险区域。
可选的，标记模块604在根据危险位置在工作区域的地图中标记危险区域时，具体用于：
根据危险位置，确定危险区域；
确定危险区域的危险类别；
根据危险区域的危险类别，以对应的标记符号，将危险区域标记在工作区域的地图中。
可选的，标记模块604在确定危险区域的危险类别时，具体用于：
接收用户的设置指令；
根据设置指令，确定危险区域的危险类别。
可选的，危险区域的类型包括：高危险区域、低危险区域；
标记模块604在根据危险区域的危险类别，以对应的标记符号，将危险区域标记在所述工作区域的地图中时，具体用于：
若危险区域的类别为高危险区域，则直接以对应的标记符号，将危险区域标记在工作区域的地图中；
若危险区域的类别为低危险区域，则将危险区域发送给用户终端，以使用户确定是否将其标记在所述工作区域的地图中。
可选的，装置600还包括规划模块606。
获取模块601还用于获取工作任务；
规划模块606用于根据工作任务、已经确定的危险区域，进行路径规划；
运行模块602用于按照规划好的路径移动。
可选的，获取模块601在获取自主移动设备的至少一个传感器采集到的传感信息时，具体用于：
获取自主移动设备中防跌落传感器采集到的距离；
处理模块603在根据传感信息，判断自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态是否为困境时，具体用于：
判断距离是否小于预设距离；
若距离大于或等于预设距离，则确定自主移动设备在获取距离时所在位置的环境状态为困境。
可选的，获取模块601在获取自主移动设备的至少一个传感器采集到的传感信息时，具体用于：
获取自主移动设备中轮降传感器被触发的传感信息；
处理模块603在根据传感信息，判断自主移动设备在获取传感信息时所在位置的环境状态或与自主移动设备在获取传感信息时所在位置相距检测距离处的环境状态是否为困境时，具体用于：
确定自主移动设备的轮降传感器被触发时，自主移动设备所在位置的环境状态为困境。
本实施例的装置，可以用于执行上述任一实施例的方法，其实现原理和技术效果类似， 此处不再赘述。
图7为本申请一实施例提供的一种自主移动设备的结构示意图，如图7所示，本实施例的自主移动设备700可以包括：存储器701和处理器702。
存储器701，用于存储程序指令。
处理器702，用于调用并执行存储器701中的程序指令，执行以上任一实施例的方法。
本实施例的自主移动设备，可以用于执行上述任一实施例的方法，其实现原理和技术效果类似，此处不再赘述。
本申请还提供了一种计算机可读存储介质，存储介质存储有计算机程序，计算机程序被处理器执行时，实现如上任一实施例的方法。
本申请实施例还提供了一种计算机程序，包括程序代码，当计算机运行所述计算机程序时，所述程序代码执行如前述任一实施例所述的方法。
本领域普通技术人员可以理解：实现上述各方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成。前述的程序可以存储于一计算机可读取存储介质中。该程序在执行时，执行包括上述各方法实施例的步骤；而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是：以上各实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述各实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例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各实施例技术方案的范围。

Claims (13)

  1. 一种困境规避方法，其特征在于，应用于自主移动设备，所述方法包括：
    获取工作区域的地图；
    所述自主移动设备在所述工作区域中运行；
    获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息能够被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
    根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；
    若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
    根据所述危险位置在所述工作区域的地图中标记危险区域；
    所述根据所述危险位置在所述工作区域的地图中标记危险区域，包括：
    根据所述危险位置，确定危险区域；
    确定所述危险区域的危险类别；
    根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中；
    所述危险区域的类型包括：高危险区域、低危险区域；
    所述根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中，包括：
    若所述危险区域的类别为高危险区域，则直接以对应的标记符号，将所述危险区域标记在所述工作区域的地图中；
    若所述危险区域的类别为低危险区域，则将所述危险区域发送给用户终端，以使用户确定是否将其标记在所述工作区域的地图中。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述危险位置在所述工作区域的地图中标记危险区域，包括：
    将包括所述危险位置的区域在所述工作区域的地图中标记为危险区域；和/或，
    获取多个彼此临近的危险位置，将包括多个彼此临近的危险位置的区域在所述工作区域的地图中标记为危险区域。
  3. 根据权利要求1或2所述的方法，其特征在于，还包括：
    根据工作区域的当前地图中的危险区域更新历史地图中的危险区域。
  4. 根据权利要求1至3中任一项所述的方法，其特征在于，
    所述确定所述危险区域的危险类别，包括：
    接收用户的设置指令；
    根据所述设置指令，确定所述危险区域的危险类别。
  5. 根据权利要求1至4中任一项所述的方法，其特征在于，还包括：
    获取工作任务；
    根据所述工作任务、已经确定的危险区域，进行路径规划；
    按照规划好的路径移动。
  6. 根据权利要求1至5中任一项所述的方法，其特征在于，
    所述获取所述自主移动设备的至少一个传感器采集到的传感信息，包括：
    获取所述自主移动设备中防跌落传感器采集到的距离；
    所述根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境，包括：
    判断所述距离是否小于预设距离；
    若所述距离大于或等于预设距离，则确定所述自主移动设备在获取所述距离时所在位置的环境状态为困境。
  7. 根据权利要求1至5中任一项所述的方法，其特征在于，
    所述获取所述自主移动设备的至少一个传感器采集到的传感信息，包括：
    获取所述自主移动设备中轮降传感器被触发的传感信息；
    所述根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境，包括：
    确定所述自主移动设备的轮降传感器被触发时，自主移动设备所在位置的环境状态为困境。
  8. 一种困境规避方法，其特征在于，应用于自主移动设备，所述方法包括：
    获取工作区域的地图；
    所述自主移动设备在所述工作区域中运行；
    获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息能够被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
    根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；
    若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
    根据所述危险位置在所述工作区域的地图中标记危险区域。
  9. 一种自主移动设备，其特征在于，包括：
    获取模块，用于获取工作区域的地图；
    运行模块，用于使所述自主移动设备在所述工作区域中运行；
    所述获取模块，还用于获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
    处理模块，用于根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
    标记模块，用于根据所述危险位置在所述工作区域的地图中标记危险区域；
    所述根据所述危险位置在所述工作区域的地图中标记危险区域，包括：
    根据所述危险位置，确定危险区域；
    确定所述危险区域的危险类别；
    根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述 工作区域的地图中；
    所述危险区域的类型包括：高危险区域、低危险区域；
    所述根据所述危险区域的危险类别，以对应的标记符号，将所述危险区域标记在所述工作区域的地图中，包括：
    若所述危险区域的类别为高危险区域，则直接以对应的标记符号，将所述危险区域标记在所述工作区域的地图中；
    若所述危险区域的类别为低危险区域，则将所述危险区域发送给用户终端，以使用户确定是否将其标记在所述工作区域的地图中。
  10. 一种自主移动设备，其特征在于，包括：
    获取模块，用于获取工作区域的地图；
    运行模块，用于使所述自主移动设备在所述工作区域中运行；
    所述获取模块，还用于获取所述自主移动设备的至少一个传感器采集到的传感信息，所述传感信息被用于得到所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态；
    处理模块，用于根据所述传感信息，判断所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态是否为困境；若确定所述自主移动设备在获取所述传感信息时所在位置的环境状态或与自主移动设备在获取所述传感信息时所在位置相距检测距离处的环境状态为困境，则将所述困境对应的位置确定为危险位置；
    标记模块，用于根据所述危险位置在所述工作区域的地图中标记危险区域。
  11. 一种自主移动设备，其特征在于，包括：
    存储器，用于存储程序指令；
    处理器，用于调用并执行所述存储器中的程序指令，执行如权利要求1-9任一项所述的方法。
  12. 一种计算机可读存储介质，其特征在于，所述存储介质存储有计算机程序，所述计算机程序被处理器执行时，实现如权利要求1-9任一项所述的方法。
  13. 一种计算机程序，其特征在于，包括程序代码，当计算机运行所述计算机程序时，所述程序代码执行如权利要求1-9任一项所述的方法。
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