WO2019062650A1 - 一种扫地机器人的控制方法及设备 - Google Patents

一种扫地机器人的控制方法及设备 Download PDF

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Publication number
WO2019062650A1
WO2019062650A1 PCT/CN2018/106808 CN2018106808W WO2019062650A1 WO 2019062650 A1 WO2019062650 A1 WO 2019062650A1 CN 2018106808 W CN2018106808 W CN 2018106808W WO 2019062650 A1 WO2019062650 A1 WO 2019062650A1
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WIPO (PCT)
Prior art keywords
cleaning
information
cleaning robot
robot
collision
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PCT/CN2018/106808
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English (en)
French (fr)
Inventor
白静
李宇翔
陈士凯
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上海思岚科技有限公司
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Publication of WO2019062650A1 publication Critical patent/WO2019062650A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
    • G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • G05D1/0253—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0259—Control of position or course in two dimensions specially adapted to land vehicles using magnetic or electromagnetic means
    • G05D1/0263—Control of position or course in two dimensions specially adapted to land vehicles using magnetic or electromagnetic means using magnetic strips
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network

Definitions

  • the present application relates to the field of computer technology, and in particular, to a control method and device for a cleaning robot.
  • An object of the present application is to provide a method and a device for controlling a cleaning robot to solve the problem of manual intervention and low cleaning efficiency of the cleaning robot in the prior art in the cleaning process.
  • a method of controlling a cleaning robot includes:
  • the cleaning task includes a cleaning strategy and a cleaning destination
  • the determining an initial position of the cleaning robot, and planning, for the cleaning robot, a global collision-free optimal path between the initial position and the cleaning destination including:
  • a global collision-free optimal path between the initial position and the cleaning destination is planned for the cleaning robot.
  • the real-time information includes real-time geographic environment information and real-time speed information of the cleaning robot.
  • the determining, according to the acquired real-time information of the cleaning robot, the global collision-free optimal path, and the cleaning strategy, determining control information when the cleaning robot performs the cleaning task including:
  • the determining, according to the cleaning policy and the collision-free movement control information, the control information when the cleaning robot performs the cleaning task includes:
  • the method further includes:
  • the positioning data information includes positioning information collected by each of the sensors in real time
  • the senor includes one or more of a laser sensor, an ultrasonic sensor, an infrared sensor, a camera, a depth sensor, an odometer, and an anti-drop sensor.
  • the method further includes:
  • the control information when the cleaning task is executed is updated.
  • a computing-based device wherein the device comprises:
  • a memory arranged to store computer executable instructions that, when executed, cause the processor to:
  • the cleaning task includes a cleaning strategy and a cleaning destination
  • a non-transitory computer readable storage medium storing executable instructions, when the executable instructions are executed by an electronic device, causing the electronic device to:
  • the cleaning task includes a cleaning strategy and a cleaning destination
  • the present application obtains a cleaning task, wherein the cleaning task includes a cleaning strategy and a cleaning destination; determining an initial position of the cleaning robot, and planning the initial position and location for the cleaning robot Determining a global collision-free optimal path between the cleaning destinations; determining, based on the acquired real-time information of the cleaning robot, the global collision-free optimal path, and the cleaning strategy, when the cleaning robot performs the cleaning task
  • the control information enables the cleaning robot to autonomously move to the cleaning destination specified by the user according to the control information when performing the cleaning task without manual intervention, and complete the cleaning task according to the cleaning strategy set by the user, which not only avoids
  • the manual intervention during the movement and cleaning process also facilitates the cleaning and cleaning process of the cleaning task by the sweeping robot and improves the cleaning efficiency of the cleaning robot.
  • FIG. 1 is a flow chart showing a control method of a cleaning robot according to an aspect of the present application
  • FIG. 2 is a block diagram showing a system for applying a control method of a cleaning robot to an intelligent cleaning of a cleaning robot according to an aspect of the present application.
  • the terminal, the device of the service network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory, such as read only memory (ROM) or flash memory (flashRAM), in a computer readable medium.
  • RAM random access memory
  • ROM read only memory
  • flashRAM flash memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage,
  • computer readable media does not include non-transitory computer readable media, such as modulated data signals and carrier waves.
  • Step S11 is a method for controlling a cleaning robot, which is applied to a cleaning robot that is installed by a user to perform a cleaning task to perform a cleaning and cleaning process of the cleaning task.
  • the method includes the step S11.
  • Step S12 and step S13, the specific steps include:
  • step S11 the cleaning task is acquired, wherein the cleaning task includes a cleaning strategy and a cleaning destination; the step S12, determining an initial position of the cleaning robot, and planning the initial position and the location for the cleaning robot Determining a global collision-free optimal path between the cleaning destinations; the step S13, determining, based on the acquired real-time information of the cleaning robot, the global collision-free optimal path, and the cleaning strategy, the execution of the cleaning robot
  • the control information of the cleaning task where the real-time information of the cleaning robot may include real-time geographic environment information and real-time speed information, etc.
  • the cleaning strategy may include a bow-shaped cleaning method, and may also include a back-shaped cleaning method.
  • the cleaning mode set based on the cleaning demand of the user may be included; the above steps S11 to S13 enable the cleaning robot to autonomously move to the cleaning destination specified by the user according to the control information when the cleaning task is executed without manual intervention. And complete the cleaning task according to the cleaning strategy set by the user, which not only avoids The manual intervention during the movement and cleaning process also facilitates the cleaning and cleaning process of the cleaning task by the sweeping robot and improves the cleaning efficiency of the cleaning robot.
  • the positioning data information includes positioning information collected by each of the sensors in real time;
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the sensor may include a laser sensor, an ultrasonic sensor, and an infrared
  • the camera can shoot and
  • Real-time geographical environment information of the environment based on the comprehensive real-time geographic environment information to determine the specific location of the global environment where the sweeping robot is located;
  • the depth sensor can detect the depth of the sweeping robot and the detection of the road condition during the moving process, etc. Achieve The detection of the road condition of the ground robot during the movement;
  • the distance of the sweeping robot can be recorded by the odometer, and the sweeping robot can be accurately positioned by the distance measuring sensor;
  • the anti-drop sensor can detect the sweeping robot passing the stairs during the moving process Tables and the like are detected to prevent the sweeping robot from falling and being broken; through one or more of the above sensors, it is possible to start from the sweeping robot and perform comprehensive detection and collection of data on the environment, thereby obtaining each of them.
  • the effective positioning data information performs real-time positioning on the sweeping robot to realize accurate real-time positioning of the sweeping robot, so that the position of the real-time positioning of the positioned sweeping robot in the global environment is more accurate.
  • the step S12 determines an initial position of the cleaning robot, and plans a global collision-free optimal path between the initial position and the cleaning destination for the cleaning robot, including:
  • Obtaining initial geographic environment information of the environment in which the cleaning robot is located for example, acquiring initial geographic environment information of the environment in which the mobile device is located by using a laser sensor, an ultrasonic sensor, an infrared sensor, a camera, a depth sensor, or the like in the cleaning robot .
  • the step S12 continues to perform location matching on the initial global environment map to obtain an initial location of the cleaning robot, wherein the global environment map is constructed from the acquired global geographic environment information.
  • the global geographic environment information may include actual geographical location information (eg, actual geographical location, latitude and longitude information, etc.) and actual environmental information (relative buildings, obstacles, actual road conditions, etc.) of the actual environment, etc.
  • the step S12 uses a preset Simultan Localization And Mapping (SLAM) algorithm to perform map construction based on the global geographic environment information in the obtained actual scene, and obtains a global environment map.
  • SLAM Simultan Localization And Mapping
  • the SLAM algorithm is used to instruct a mobile device (such as a cleaning robot, etc.) to start from an unknown location of an unknown environment, and to locate its position and posture by repeatedly observing geographical environment information (such as a corner, a pillar, etc.) during the movement, according to its own position. Incremental construction of the map to achieve the same The purpose of locating and mapping.
  • the initial geographic environment information is matched in the global environment map by using a related map matching algorithm, a road matching algorithm, etc., and the sweeping robot is obtained in the global environment map.
  • An initial position of the sweeping robot in the global environment map to achieve accurate positioning of the sweeping robot, so as to be able to know in real time that the sweeping robot is in its place The specific positioning position in the actual global environment: the initial position, the purpose of the initial precise positioning of the sweeping robot is achieved.
  • the step S12 continues to plan a global collision-free optimal path between the initial position and the cleaning destination for the cleaning robot based on the virtual wall information preset by the user and the global environment map.
  • the user can set, add or delete any shape of the preset virtual wall information with the pass-through rule through a graphical editing environment (for example, an editing interface of the virtual wall information, etc.), and the preset The virtual wall information is sent to the cleaning robot so that the cleaning robot avoids obstacles in the actual global environment through the user-preset virtual wall information.
  • the virtual wall information preset by the user and the global environment map are started from the initial position, and a preset heuristic search algorithm is used to plan for the sweeping robot on the global environment map.
  • a global collision-free optimal path between the initial position and the cleaning destination so that the preset virtual wall information can be used to generate additional auxiliary hardware devices at no additional cost to perform path planning for the cleaning task, so that the cleaning robot
  • the use is more convenient, flexible and fast, thereby saving the cost of manpower and material resources, and at the same time, virtual reality obstacles are obtained through preset virtual wall information, thereby avoiding changing the real environment, so that the virtual wall information based on the preset is in the global environment map. It is more convenient and intelligent to plan and clean out the global collision-free optimal path for the cleaning task, so that the global collision-free optimal path selected by the planning is more accurate and faster.
  • the real-time information may include: real-time geographic environment information and real-time speed information of the cleaning robot, wherein the real-time speed information may include, but is not limited to, real-time speed v, real-time acceleration a, and real-time angular velocity.
  • the step S13 based on the acquired real-time information of the cleaning robot, the global collision-free optimal path, and the cleaning policy, determining control information when the cleaning robot performs the cleaning task, including:
  • the mobile device includes one or more of a moving speed, a moving direction, environmental parameter information (such as road conditions, wind speed, etc.) and movement smoothness information when the mobile device moves in real time.
  • the real-time real-time environment can be obtained by sensors such as a laser sensor, an ultrasonic sensor, an infrared sensor, a positioning sensor (such as a GPS positioning sensor), a camera device, and a depth sensor in the cleaning robot.
  • the real-time speed information of the geographical environment information and the mobile device, the real-time geographic environment information acquired by all the sensors (including the real-time positioning position) is combined and combined with the real-time speed information of the mobile device, and the dynamic window of the local obstacle avoidance of the mobile device is utilized.
  • the algorithm when moving from the initial position of the cleaning robot and moving according to the global collision-free optimal path determined in the step S12, determining the corresponding collision-free movement information during the movement, so that the cleaning robot can be based on the collision-free movement information.
  • the collision-free completion is started from the initial position where the cleaning robot receives the cleaning task and moves to the movement path of the cleaning destination.
  • the step S13 continues to generate collision-free movement control information based on the collision-free movement information and the movement model of the cleaning robot, for example, different movement models corresponding to different mobile devices, and completes the cleaning robot from the initial position to the cleaning. Collision-free movement control of the movement process between the destinations; then determining control information when the cleaning robot executes the cleaning task based on the cleaning strategy and the collision-free movement control information, so that the cleaning robot can be controlled according to the control The information is run without collision during the moving process of the cleaning task and the cleaning process, thereby completing the cleaning task set by the user on the cleaning robot.
  • the determining, in the step S13, the control information when the cleaning robot performs the cleaning task based on the cleaning policy and the collision-free movement control information includes:
  • the collision-free cleaning information may include one or more of a cleaning speed, a cleaning direction, a cleaning point, and a cleaning movement smoothness, wherein the cleaning point is determined by the cleaning range and a sweeping diameter of the cleaning robot.
  • the cleaning strategy is a bow-shaped cleaning method
  • the sweeping robot completes the environmental detection in the cleaning range according to the real-time information carried in the cleaning task according to the cleaning range in the cleaning task, and combines the real-time geographical environment information of the lap.
  • the cleaning destination is used as the starting position of the cleaning, according to the cleaning range and the cleaning of the cleaning robot Diameter, from inside to outside, planning a collision-free cleaning point, complete Planning and determining a cleaning point in the cleaning range; then generating collision-free cleaning control information based on the collision-free cleaning information in the cleaning process and the moving model of the cleaning robot, so that the cleaning robot can be based on
  • the collision-free cleaning control information clears the collision-free cleaning process for the cleaning range, thereby completing the cleaning task set by the user on the cleaning robot; finally, based on controlling the cleaning robot to move from the initial position to the cleaning destination in the cleaning task.
  • the collision-free movement control information of the movement process and the collision-free cleaning control information for controlling the cleaning process of the cleaning of the sweeping robot in the cleaning range to determine the control information when the cleaning robot executes the cleaning task.
  • the control information when the cleaning task is executed is updated. For example, if a temporary obstacle is generated during the movement from the initial position to the cleaning destination during the movement of the user-set cleaning task and/or during the cleaning of the cleaning cleaning range, the previously planned control of the cleaning robot moves. The process of cleaning and/or cleaning cannot be performed normally. In order to ensure the normal completion of the cleaning task, the planned control information when the cleaning task is executed needs to be updated to satisfy the smooth execution of the cleaning robot and complete the cleaning task.
  • FIG. 2 is a schematic diagram of interaction between a control method of a sweeping robot applied to a smart sweeping system of a sweeping robot according to an aspect of the present application, the system includes a sweeping robot end and a user end, wherein the sweeping robot consists of four parts.
  • the metering module includes: a cleaning task module for setting a fixed point, a global path planning module, a partial path planning module, a motion control module, and an intelligent movement module, wherein the partial cleaning part includes a cleaning point generation module, Sweep module and exception handling module.
  • the cleaning task is set in the user interaction module through the visual interface, and the cleaning task is forwarded to the cleaning robot through the communication module, so that the task management scheduling module in the cleaning robot is set to the user.
  • the specific cleaning task is managed and scheduled; wherein the specific execution process of each module in the cleaning robot is as follows:
  • SLAM autonomous positioning part mainly used to build a global environment map, and obtain the current location according to the global environment map and real-time information. Specifically:
  • Map module It is mainly used to construct a global environment map based on the real-time acquired global geographic environment information by using the preset SLAM algorithm, so as to plan a global collision-free optimal path for the cleaning task of the sweeping robot based on the global environment map. Real-time positioning of the sweeping robot.
  • the autonomous positioning module obtains initial geographical environment information of the environment in which the mobile device is located by using a laser sensor, an ultrasonic sensor, an infrared sensor, a camera device, a depth sensor, and a fall prevention sensor in the cleaning robot; and then adopts related map matching An algorithm, a road matching algorithm, or the like, performs location matching on the global environment map to obtain an initial position of the cleaning robot in the global environment map; wherein the initial location is Determining the position of the sweeping robot in the global environment map to realize the positioning of the sweeping robot, and then real-time knowing the specific positioning position of the sweeping robot in the actual global environment in which it is located: the initial position, The purpose of initial positioning of the sweeping robot is achieved.
  • Data acquisition part It is mainly used to collect positioning information such as laser sensor, infrared sensor and odometer for positioning, so as to obtain effective and effective positioning position information, and realize real-time positioning of the cleaning robot. Specifically:
  • a data filtering module acquiring real-time positioning data information of the cleaning robot by using at least one sensor, wherein the positioning data information includes positioning information collected by each of the sensors in real time; where the sensor may include a laser sensor, One or more of an ultrasonic sensor, an infrared sensor, a depth sensor, and an anti-drop sensor; the data in the collected positioning information is data-processed by pre-processing one or more of the sensor data collected Filtering, eliminating noise data, reducing false triggering, for example, avoiding the false data triggered by the anti-drop sensor triggering the false trigger of the sweeping robot to retreat or stop, and realize the correct operation of the sweeping robot in the global environment.
  • the odometer module is used to record the distance moved by the sweeping robot through the odometer, and the positioning robot can be accurately positioned with the distance measuring sensor.
  • the main purpose is to move the robot autonomously to the destination to be cleaned according to the global environment map and real-time information, avoiding manual intervention, improving the autonomous mobility of the sweeping robot, and improving the sweeping efficiency. Specifically:
  • the mobile terminal application sends a cleaning task to the cleaning robot to clean the destination to be cleaned.
  • a global path planning module according to the determined initial position of the cleaning robot, starting from the initial position, using a heuristic search algorithm on the global environment map, planning the initial position and the Clean the global collision-free best path between the destinations to guide the sweeping robot to complete the user-defined cleaning task.
  • the actual environment can be obtained by sensors such as laser sensors, ultrasonic sensors, infrared sensors, positioning sensors (such as GPS positioning sensors), camera devices and depth sensors in the sweeping robot.
  • sensors such as laser sensors, ultrasonic sensors, infrared sensors, positioning sensors (such as GPS positioning sensors), camera devices and depth sensors in the sweeping robot.
  • Real-time geographic environment information and real-time speed information of mobile devices real-time geographic environment information (including real-time location) acquired by all sensors is combined and combined with real-time speed information of mobile devices, and local obstacle avoidance of mobile devices is utilized
  • the dynamic window algorithm from the initial position of the cleaning robot, when moving according to the global collision-free optimal path determined in the step S12, the determined collision-free movement information corresponding to the movement, so that the cleaning robot can be based on the collision-free
  • the movement information, the completion of the collision-free completion is started from the initial position where the cleaning robot receives the cleaning task and moves to the movement path of the cleaning destination.
  • a motion control module generating collision-free movement control information based on the collision-free movement information and a movement model of the cleaning robot, for example, different movement models corresponding to different mobile devices, completing the cleaning robot from an initial position to a cleaning purpose Collision-free movement control of the movement process between the grounds.
  • Intelligent mobile module receiving collision-free movement control information, and controlling the movement process of the cleaning robot between the initial position and the cleaning destination can be moved without collision.
  • Partial cleaning part The main purpose is to use the global environment map and real-time information according to the set cleaning strategy, plan the cleaning points in the cleaning range, design the cleaning strategy, and complete the cleaning task. Specifically:
  • a cleaning point generating module a cleaning range in the cleaning task and a sweeping diameter of the cleaning robot determine a cleaning point when cleaning the cleaning range; if the cleaning strategy is a bow cleaning mode, the cleaning robot according to the real-time information carried According to the cleaning range in the cleaning task, the edge is completed to detect the environment within the cleaning range, and the real-time geographical environment information of the lap and the sweeping diameter of the sweeping robot are combined to plan a cleaning point without collision; if the cleaning strategy is back In the glyph cleaning mode, the current position of the sweeping robot is directly used: the cleaning destination is used as the starting position of the cleaning, and according to the cleaning range and the cleaning diameter of the cleaning robot, the cleaning point is prepared from the inside to the outside, and the cleaning point is completed within the cleaning range. Planning and determination of cleaning points.
  • a cleaning module generating the collision-free cleaning control information based on the collision-free cleaning information during the cleaning of the cleaning range and the movement model of the cleaning robot, so that the cleaning robot can complete the cleaning according to the collision-free cleaning control information
  • the collision-free cleaning process of the range is performed to complete the cleaning task set by the user on the cleaning robot; and finally the collision-free movement control information based on the movement process between the cleaning position of the cleaning robot moving from the initial position to the cleaning task is controlled.
  • the collision-free cleaning control information for controlling a cleaning process in which the cleaning robot performs the sweeping in the cleaning range, and determining control information when the cleaning robot executes the cleaning task.
  • Exception handling module If during the movement from the initial position to the cleaning destination during the cleaning task of the user setting and/or during the cleaning process of the cleaning and cleaning range, temporary obstacles appear, resulting in the previously planned control sweeping The process of moving and/or cleaning the robot cannot be performed normally. In order to ensure the normal completion of the cleaning task, the planned control information when the cleaning task is executed needs to be updated to meet the cleaning performance of the cleaning robot and complete the cleaning. task.
  • another aspect of the present application provides a computing-based device, wherein the device includes:
  • a memory arranged to store computer executable instructions that, when executed, cause the processor to:
  • the cleaning task includes a cleaning strategy and a cleaning destination
  • Another aspect of the present application also provides a non-transitory computer readable storage medium storing executable instructions, when the executable instructions are executed by an electronic device, causing the electronic device to:
  • the cleaning task includes a cleaning strategy and a cleaning destination
  • the present invention provides a method and apparatus for controlling a cleaning robot, by acquiring a cleaning task, wherein the cleaning task includes a cleaning strategy and a cleaning destination; and determining an initial position of the cleaning robot,
  • the sweeping robot plans a global collision-free optimal path between the initial position and the cleaning destination; determining based on the acquired real-time information of the cleaning robot, the global collision-free optimal path, and the cleaning strategy
  • the control information when the cleaning robot executes the cleaning task enables the cleaning robot to autonomously move to the cleaning destination specified by the user according to the control information when performing the cleaning task without manual intervention, and set according to the user.
  • the cleaning strategy completes the cleaning task, which not only avoids manual intervention during the movement and cleaning process, but also facilitates the cleaning and cleaning process of the cleaning task by the sweeping robot, and improves the cleaning efficiency of the cleaning robot.
  • the present application can be implemented in software and/or a combination of software and hardware, for example, using an application specific integrated circuit (ASIC), a general purpose computer, or any other similar hardware device.
  • the software program of the present application can be executed by a processor to implement the steps or functions described above.
  • the software programs (including related data structures) of the present application can be stored in a computer readable recording medium such as a RAM memory, a magnetic or optical drive or a floppy disk and the like.
  • some of the steps or functions of the present application may be implemented in hardware, for example, as a circuit that cooperates with a processor to perform various steps or functions.
  • a portion of the present application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide a method and/or technical solution in accordance with the present application.
  • the program instructions for invoking the method of the present application may be stored in a fixed or removable recording medium, and/or transmitted by a data stream in a broadcast or other signal bearing medium, and/or stored in a The working memory of the computer device in which the program instructions are run.
  • an embodiment in accordance with the present application includes a device including a memory for storing computer program instructions and a processor for executing program instructions, wherein when the computer program instructions are executed by the processor, triggering
  • the apparatus operates based on the aforementioned methods and/or technical solutions in accordance with various embodiments of the present application.

Abstract

一种扫地机器人的控制方法及设备，控制方法包括，获取清扫任务，其中，清扫任务包括清扫策略和清扫目的地（S11）；确定扫地机器人的初始位置，为扫地机器人规划出初始位置与清扫目的地之间的全局无碰撞最佳路径（S12）；基于获取的扫地机器人的实时信息、全局无碰撞最佳路径和清扫策略，确定扫地机器人执行清扫任务时的控制信息（S13）。不仅避免了移动和清扫过程中的人工干预，还方便了扫地机器人完成清扫任务的移动和清扫过程，并提高了扫地机器人的清扫效率。

Description

一种扫地机器人的控制方法及设备 技术领域
本申请涉及计算机技术领域，尤其涉及一种扫地机器人的控制方法及设备。
背景技术
随着廉价激光传感器的落地，携带激光传感器的扫地机也应用而生。针对局部清扫方式，目前各个扫地机厂商采取的主流方式是：将机器抱至或手动遥控至待清扫区域，通过app交互，根据预设定的清扫范围，开始定点清扫，且清扫方式为先贴边，然后根据探测到的环境信息，开始弓字形清扫。该种方式需要人工干预，不能体现其智能感知移动性，且固定清扫方式，有可能将局部清扫区域的垃圾打到清扫区域外，不能高效快捷地完成局部清扫任务，因此，如何方便快捷地使扫地机器人完成用户的清扫任务成为业界主要研究的课题。
发明内容
本申请的一个目的是提供一种扫地机器人的控制方法及设备，以解决现有技术中的扫地机器人在清扫过程中的人工干预和清扫效率低的问题。
根据本申请的一个方面，提供了一种扫地机器人的控制方法，其中，所述方法包括：
获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
进一步地，上述方法中，所述确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径，包括：
获取所述扫地机器人所处环境的初始地理环境信息；
将所述初始地理环境信息在构建的全局环境地图中进行位置匹配，得到所述扫地机器人的初始位置，其中，所述全局环境地图由获取的全局地理环境信息构建得到。
基于用户预设的虚拟墙信息和所述全局环境地图，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径。
进一步地，上述方法中，所述实时信息包括：所述扫地机器人的实时地理环境信息和实时速度信息。
进一步地，上述方法中，所述基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人按照所述全局无碰撞最佳路径进行移动时的无碰撞移动信息；
基于所述无碰撞移动信息和所述扫地机器人的移动模型，生成无碰撞移动控制信息；
基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
进一步地，上述方法中，所述基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人在所述清扫任务中的清扫范围内，按照所述清扫策略进行移动时的无碰撞清扫信息；
基于所述无碰撞清扫信息和所述扫地机器人的移动模型，生成无碰撞清扫控制信息；
基于所述无碰撞移动控制信息和所述无碰撞清扫控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
进一步地，上述方法中，所述方法还包括：
通过至少一个传感器获取所述扫地机器人的实时的定位数据信息，其中，所述定位数据信息包括每一个所述传感器实时采集的定位信息；
对所述定位位置信息中的所有所述定位信息进行过滤，得到所述扫地机器人的有效定位数据信息；
根据所述有效定位数据信息对所述扫地机器人进行实时定位。
进一步地，上述方法中，所述传感器包括激光传感器、超声传感器、红外传感器、摄像装置、深度传感器、里程计及防跌落传感器中的一项或多项。
进一步地，上述方法中，所述方法还包括：
对执行所述清扫任务时的所述控制信息进行更新。
根据本申请的另一方面，还提供了一种基于计算的设备，其中，该设备包括：
处理器；以及
被安排成存储计算机可执行指令的存储器，所述可执行指令在被执行时使所述处理器：
获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
根据本申请的另一方面，还提供了一种存储可执行指令的非暂态计算机可读存储介质，在所述可执行指令由电子设备执行时，使得所述电子设备：
获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
与现有技术相比，本申请通过获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，使得扫地机器人能够在无人工干预的情况下，根据执行清扫任务时的控制信息，自主移动至用户指定的清扫目的地，并按照用户设定的清扫策略完成清扫任务，不仅避免了移动和清扫过程中的人工干预，还方便了扫地机器人完成清扫任务的移动和清扫过程，并提高了扫地机器人的清扫效率。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本申请的其它特征、目的和优点将会变得更明显：
图1示出根据本申请一个方面的一种扫地机器人的控制方法的流程示意图；
图2示出根据本申请的一个方面的将扫地机器人的控制方法应用于扫地机器人的智能清扫的系统的结构示意图。
附图中相同或相似的附图标记代表相同或相似的部件。
具体实施方式
下面结合附图对本申请作进一步详细描述。
在本申请一个典型的配置中，终端、服务网络的设备和可信方均包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flashRAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括非暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
图1根据本申请的一个方面，提供了一种扫地机器人的控制方法，应用于扫地机器人随时接到用户设置的清扫任务以执行完成该清扫任务的移动和清扫过程中，该方法包括步骤S11、步骤S12和步骤S13，具体步骤包括：
所述步骤S11，获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；所述步骤S12，确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；所述步骤S13，基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，在此，所述扫地机器人的实时信息可以包括实时地理环境信息和实时速度信息等，所述清扫策略可以包括弓字形清扫方式，也可以包括回字形清扫方式， 也可以包括基于用户的清扫需求设置的清扫方式；上述步骤S11至步骤S13使扫地机器人能够在无人工干预的情况下，根据执行清扫任务时的控制信息，自主移动至用户指定的清扫目的地，并按照用户设定的清扫策略完成清扫任务，不仅避免了移动和清扫过程中的人工干预，还方便了扫地机器人完成清扫任务的移动和清扫过程，并提高了扫地机器人的清扫效率。
本申请一实施例中的一种扫地机器人的控制方法还包括：
通过至少一个传感器获取所述扫地机器人的实时的定位数据信息，其中，所述定位数据信息包括每一个所述传感器实时采集的定位信息；在此，所述传感器可以包括激光传感器、超声传感器、红外传感器、摄像装置、深度传感器、里程计及防跌落传感器中的一项或多项，其中，通过激光传感器、超声传感器及红外传感器不进可以检测到所述扫地机器人在移动过程中的障碍物，还可以检测障碍物距离扫地机器人的距离等，以使扫地机器人基于对障碍物的测距避免移动至障碍物处，实现无碰撞的移动；通过摄像装置可以360度或者270度拍摄并采集扫地机器人所处环境的实时地理环境信息，基于全方位的实时地理环境信息确定扫地机器人所处全局环境的具体位置；通过深度传感器可以检测扫地机器人在移动过程中的路面深度及道路情况的探测等，以实现对扫地机器人的在移动过程中的路况的探测；通过里程计可以记录扫地机器人移动的距离，可以结合测距的传感器对扫地机器人进行精确定位；通过防跌落传感器可以探测扫地机器人在移动过程中经过楼梯桌子等进行探测，避免扫地机器人跌落而摔碎；通过上述传感器中的一项甚至是多项，可以从扫地机器人出发，对所处环境进行数据的全面检测并采集，进而可以得到包括有每一个所述传感器实时采集的定位信息的定位数据信息；为了对扫地机器人进行精确定位，需要对所述定位位置信息中的所有所述定位信息进行过滤，得到所述扫地机器人的有效定位数据信息；根据所述有效定位数据信息对所述扫地机器人进行实时定位，实现对扫地机器人的精准的实时定位，使得定位得到的扫地机器人的实时定位的位置在全局环境中的位置更加 精准。
本申请一实施例中，所述步骤S12确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径，包括：
获取所述扫地机器人所处环境的初始地理环境信息；例如，通过扫地机器人中的激光传感器、超声传感器、红外传感器、摄像装置及深度传感器等来获取所述移动设备所处环境的初始地理环境信息。
之后，所述步骤S12继续将所述初始地理环境信息在构建的全局环境地图中进行位置匹配，得到所述扫地机器人的初始位置，其中，所述全局环境地图由获取的全局地理环境信息构建得到；在此，所述全局地理环境信息可以包括实际场景中的实际地理位置信息(例如实际地理定位位置、经纬度信息等)和实际环境信息(实际环境的相对建筑、障碍物及实际路况等)等，例如，所述步骤S12采用预设的同步定位于地图构建(Simultanous Localization And Mapping，SLAM)算法，基于获取的实际场景中的全局地理环境信息进行地图构建，得到全局环境地图，其中，所述SLAM算法用于指示使移动设备(例如扫地机器人等)从未知环境的未知地点出发，在运动过程中通过重复观测的地理环境信息(例如墙角、柱子等)定位自身位置和姿态，在根据自身位置增量式的构建地图，从而达到同时定位和地图构建的目的。
在得到全局环境地图之后，采用相关的地图匹配算法、道路匹配算法等，将所述初始地理环境信息在所述全局环境地图中进行位置匹配，得到所述扫地机器人在所述全局环境地图中所处的初始位置；其中，该初始位置为所述扫地机器人当前在所述全局环境地图中的自身定位位置，以实现对所述扫地机器人的精准定位，进而能够实时获悉该扫地机器人在自己所处的实际全局环境中的具体定位位置：初始位置，达到对所述扫地机器人进行最初的精准定位的目的。
接着，所述步骤S12继续基于用户预设的虚拟墙信息和所述全局环境地 图，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径。在此，用户可以通过图形化的编辑环境(例如虚拟墙信息的编辑界面等)，设定、添加或者删除任意形状的带有通过性规则的预设的虚拟墙信息，并将该预设的虚拟墙信息发送至该扫地机器人处，以便扫地机器人通过用户预设的虚拟墙信息避免撞上实际全局环境中的障碍物。例如，所述步骤S12用户预设的虚拟墙信息和所述全局环境地图，从所述初始位置开始，采用预设的启发式搜索算法，在所述全局环境地图上为所述扫地机器人规划出所述初始位置至清扫目的地之间的全局无碰撞最佳路径，使得通过预设的虚拟墙信息能够在不需要额外的成本生产额外辅助的硬件设备来为清扫任务进行路径规划，使得扫地机器人使用更加的方便、灵活、快捷，从而节省了人力物力等成本，同时通过预设的虚拟墙信息来虚拟现实的障碍物，避免了改变现实环境，使得基于预设的虚拟墙信息在全局环境地图上为清扫任务规划并筛选出全局无碰撞最佳路径的过程更加方便和智能化，使得规划筛选出的全局无碰撞最佳路径更精确快捷。
接着本申请的上述实施例，所述实时信息可以包括：所述扫地机器人的实时地理环境信息和实时速度信息，其中，实时速度信息可以包括但不限于是实时速度v，实时加速度a及实时角速度w等，所述步骤S13基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人按照所述全局无碰撞最佳路径进行移动时的无碰撞移动信息；其中，其中，该无碰撞移动信息可以包括所述移动设备实时移动时的移动速度、移动方向、环境参数信息(例如道路情况、风速等)及移动平稳度信息中的一项或多项等。例如，在扫地机器人移动的实际场景中，可以通过扫地机器人中的激光传感器、超声传感器、红外传感器、定位传感器(例如GPS定位传感器等)、摄像装置及深度传感器等传感器来获取实际环境中的实 时地理环境信息和移动设别的实时速度信息，将所有的传感器获取的实时地理环境信息(包括实时定位位置)进行融合并结合移动设备的实时速度信息，并利用移动设备的局部避障的动态窗口算法，从扫地机器人的初始位置开始，按照所述步骤S12中确定的全局无碰撞最佳路径进行移动时，确定的移动时对应的无碰撞移动信息，使得扫地机器人可以基于该无碰撞移动信息，无碰撞的完成从扫地机器人收到清扫任务的初始位置开始移动至清扫目的地的移动路径的导航。
所述步骤S13继续基于所述无碰撞移动信息和所述扫地机器人的移动模型例如，不同的移动设备对应的移动模型不同)，生成无碰撞移动控制信息，完成所述扫地机器人从初始位置至清扫目的地之间的移动过程的无碰撞移动控制；接着基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息，使得扫地机器人能够根据该控制信息在完成清扫任务的移动过程和清扫过程中无碰撞的运行，进而完成用户在扫地机器人上设置的清扫任务。
接着本申请的上述实施例，所述步骤S13中的基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人在所述清扫任务中的清扫范围内，按照所述清扫策略进行移动时的无碰撞清扫信息；在此，所述无碰撞清扫信息可以包括清扫速度、清扫方向、清扫点及清扫移动平稳度中的一项或多项，其中，所述清扫点由所述清扫范围和所述扫地机器人的扫地直径确定，例如，若清扫策略为弓字形清扫方式，则扫地机器人根据所携带的实时信息，根据清扫任务中的清扫范围，贴边完成该清扫范围内的环境探测，结合贴边一圈的实时地理环境信息以及扫地机器人的扫地直径，规划出无碰撞的清扫点；若清扫策略为回字形清扫方式，则直接将扫地机器人的当前位置：清扫目的地作为清扫的起点位 置，根据清扫范围和扫地机器人的清扫直径，由内向外，规划出无碰撞的清扫点，完成对清扫范围内的清扫点的规划与确定；接着基于对清扫范围进行清扫的过程中的所述无碰撞清扫信息和所述扫地机器人的移动模型，生成无碰撞清扫控制信息，使得扫地机器人能够根据该无碰撞清扫控制信息清完成对清扫范围进行的无碰撞清扫过程，进而完成用户在扫地机器人上设置的清扫任务；最后基于控制扫地机器人从初始位置移动至清扫任务中的清扫目的地之间的移动过程的所述无碰撞移动控制信息和控制扫地机器人在清扫范围内进行扫地的清扫过程的所述无碰撞清扫控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
本申请一实施例中的一种扫地机器人的控制方法，还包括：
对执行所述清扫任务时的所述控制信息进行更新。例如，若在执行用户设置的清扫任务时的从初始位置移动至清扫目的地的移动过程中和/或在清扫清扫范围的清扫过程中，出现临时障碍物，导致之前规划出的控制扫地机器人移动和/或清扫的过程无法正常进行，为了保证清扫任务的正常完成，则需要对规划出的执行所述清扫任务时的所述控制信息进行更新，以满足扫地机器人能够顺利执行并完成清扫任务。
如图2所示为本申请一个方面的一种将扫地机器人的控制方法应用于扫地机器人的智能清扫的系统的交互示意图，该系统包括扫地机器人端和用户端，其中，该扫地机器人由四部分组成，自主移动至清扫目的地部分、局部清扫部分、SLAM自主定位部分及数据采集部分，其中，所述SLAM自主定位部分包括自主定位模块和地图模块，所述数据采集部分包括数据滤波模块和里程计模块，所述自主移动至清扫目的地部分包括设定定点的清扫任务模块、全局路径规划模块、局部路径规划模块、运动控制模块及智能移动模块，所述局部清扫部分包括清扫点生成模块、清扫模块和异常处理模块。当用户需要读某一目的地进行清扫时，通过可视化界面在用户交互模块设定清扫任务，并通过通信模块将该清扫任务转发至扫地机器人中，以便扫地机器人中 的任务管理调度模块对用户设定的清扫任务进行管理和调度；其中，该扫地机器人中的各个模块的具体执行过程如下：
SLAM自主定位部分：主要用于构建全局环境地图，并根据全局环境地图和实时信息获得当前位置。具体为：
地图模块：主要用于采用预设的SLAM算法基于实时获取的全局地理环境信息构建地图得到全局环境地图，以便后续基于该全局环境地图为扫地机器人的清扫任务规划全局无碰撞最佳路径并实现对扫地机器人的实时定位。
自主定位模块：通过扫地机器人中的激光传感器、超声传感器、红外传感器、摄像装置、深度传感器及防跌落传感器等来获取所述移动设备所处环境的初始地理环境信息；之后，采用相关的地图匹配算法、道路匹配算法等，将所述初始地理环境信息在所述全局环境地图中进行位置匹配，得到所述扫地机器人在所述全局环境地图中所处的初始位置；其中，该初始位置为所述扫地机器人当前在所述全局环境地图中的自身定位位置，以实现对所述扫地机器人的定位，进而能够实时获悉该扫地机器人在自己所处的实际全局环境中的具体定位位置：初始位置，达到对所述扫地机器人进行最初的定位的目的。
数据采集部分：主要用于采集激光传感器、红外传感器及里程计等用于进行定位的定位位置信息，以便得到有效的有效定位位置信息，进而实现对扫地机器人的实时定位。具体为：
数据滤波模块：通过至少一个传感器获取所述扫地机器人的实时的定位数据信息，其中，所述定位数据信息包括每一个所述传感器实时采集的定位信息；在此，所述传感器可以包括激光传感器、超声传感器、红外传感器、深度传感器及防跌落传感器中的一项或多项；通过对上述传感器中的一项甚至是多项采集的传感器数据进行预处理，将采集的定位信息中的数据进行数据过滤，剔除噪点数据，减少误触发，例如，避免防跌落传感器采集的噪点数据触发扫地机器人后退或者停止等误触发，实现对扫地机器人在全局环境 中的正确操作。
里程计模块，用于通过里程计可以记录扫地机器人移动的距离，可以结合测距的传感器对扫地机器人进行精确定位。
自主移动至清扫目的地部分：主要目的是根据全局环境地图及实时信息，将机器人自主移动至待清扫的目的地，避免人工干预，提升扫地机器人自主移动性，且提升扫地效率。具体为：
设定定点局部清扫任务模块：根据实际家居环境和用户需求等，由手机端应用程序向扫地机器人下发对需要清扫的目的地进行清扫的清扫任务。
全局路径规划模块：根据确定的所述扫地机器人的初始位置，从所述初始位置开始，采用启发式搜索算法在所述全局环境地图上，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径，以指引扫地机器人完成用户设定的清扫任务。
局部路径规划模块：在扫地机器人移动的实际场景中，可以通过扫地机器人中的激光传感器、超声传感器、红外传感器、定位传感器(例如GPS定位传感器等)、摄像装置及深度传感器等传感器来获取实际环境中的实时地理环境信息和移动设别的实时速度信息，将所有的传感器获取的实时地理环境信息(包括实时定位位置)进行融合并结合移动设备的实时速度信息，并利用移动设备的局部避障的动态窗口算法，从扫地机器人的初始位置开始，按照所述步骤S12中确定的全局无碰撞最佳路径进行移动时，确定的移动时对应的无碰撞移动信息，使得扫地机器人可以基于该无碰撞移动信息，无碰撞的完成从扫地机器人收到清扫任务的初始位置开始移动至清扫目的地的移动路径的导航。
运动控制模块：基于所述无碰撞移动信息和所述扫地机器人的移动模型例如，不同的移动设备对应的移动模型不同)，生成无碰撞移动控制信息，完成所述扫地机器人从初始位置至清扫目的地之间的移动过程的无碰撞移动控制。
智能移动模块：接收无碰撞移动控制信息，控制扫地机器人在初始位置至清扫目的地之间的移动过程能够无碰撞移动。
局部清扫部分：主要目的是根据设定的清扫策略，利用全局环境地图及实时信息，规划清扫范围内的清扫点，设计清扫策略，完成清扫任务。具体为：
清扫点生成模块：所述清扫任务中的清扫范围和所述扫地机器人的扫地直径确定对清扫范围进行清扫时的清扫点；若清扫策略为弓字形清扫方式，则扫地机器人根据所携带的实时信息，根据清扫任务中的清扫范围，贴边完成该清扫范围内的环境探测，结合贴边一圈的实时地理环境信息以及扫地机器人的扫地直径，规划出无碰撞的清扫点；若清扫策略为回字形清扫方式，则直接将扫地机器人的当前位置：清扫目的地作为清扫的起点位置，根据清扫范围和扫地机器人的清扫直径，由内向外，规划出无碰撞的清扫点，完成对清扫范围内的清扫点的规划与确定。
清扫模块：基于对清扫范围进行清扫的过程中的所述无碰撞清扫信息和所述扫地机器人的移动模型，生成无碰撞清扫控制信息，使得扫地机器人能够根据该无碰撞清扫控制信息清完成对清扫范围进行的无碰撞清扫过程，进而完成用户在扫地机器人上设置的清扫任务；最后基于控制扫地机器人从初始位置移动至清扫任务中的清扫目的地之间的移动过程的所述无碰撞移动控制信息和控制扫地机器人在清扫范围内进行扫地的清扫过程的所述无碰撞清扫控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
异常处理模块：若在执行用户设置的清扫任务时的从初始位置移动至清扫目的地的移动过程中和/或在清扫清扫范围的清扫过程中，出现临时障碍物，导致之前规划出的控制扫地机器人移动和/或清扫的过程无法正常进行，为了保证清扫任务的正常完成，则需要对规划出的执行所述清扫任务时的所述控制信息进行更新，以满足扫地机器人能够顺利执行并完成清扫任务。
此外，本申请的另一方面还提供了一种基于计算的设备，其中，该设备 包括：
处理器；以及
被安排成存储计算机可执行指令的存储器，所述可执行指令在被执行时使所述处理器：
获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
本申请的另一方面还提供了一种存储可执行指令的非暂态计算机可读存储介质，在所述可执行指令由电子设备执行时，使得所述电子设备：
获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
综上所述，本申请提供的一种扫地机器人的控制方法及设备，通过获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，使得扫地机器人能够在无人工干预的情况下，根据执行清扫任务时的控制信息，自主移动至用户指定的清扫目的地，并按照用户设定的清扫策略完成清扫任务，不仅避免了移动和清扫过程中的人工干预，还方便了扫地机器人完成清扫任务的移动和清扫过程，并提高了扫地机器人的清扫效率。
需要注意的是，本申请可在软件和/或软件与硬件的组合体中被实施，例如，可采用专用集成电路(ASIC)、通用目的计算机或任何其他类似硬件设备来实现。在一个实施例中，本申请的软件程序可以通过处理器执行以实现上文所述步骤或功能。同样地，本申请的软件程序(包括相关的数据结构)可以被存储到计算机可读记录介质中，例如，RAM存储器，磁或光驱动器或软磁盘及类似设备。另外，本申请的一些步骤或功能可采用硬件来实现，例如，作为与处理器配合从而执行各个步骤或功能的电路。
另外，本申请的一部分可被应用为计算机程序产品，例如计算机程序指令，当其被计算机执行时，通过该计算机的操作，可以调用或提供根据本申请的方法和/或技术方案。而调用本申请的方法的程序指令，可能被存储在固定的或可移动的记录介质中，和/或通过广播或其他信号承载媒体中的数据流而被传输，和/或被存储在根据所述程序指令运行的计算机设备的工作存储器中。在此，根据本申请的一个实施例包括一个装置，该装置包括用于存储计算机程序指令的存储器和用于执行程序指令的处理器，其中，当该计算机程序指令被该处理器执行时，触发该装置运行基于前述根据本申请的多个实施例的方法和/或技术方案。
对于本领域技术人员而言，显然本申请不限于上述示范性实施例的细节，而且在不背离本申请的精神或基本特征的情况下，能够以其他的具体形式实现本申请。因此，无论从哪一点来看，均应将实施例看作是示范性的，而且是非限制性的，本申请的范围由所附权利要求而不是上述说明限定，因此旨在将落在权利要求的等同要件的含义和范围内的所有变化涵括在本申请内。不应将权利要求中的任何附图标记视为限制所涉及的权利要求。此外，显然“包括”一词不排除其他单元或步骤，单数不排除复数。装置权利要求中陈述的多个单元或装置也可以由一个单元或装置通过软件或者硬件来实现。第一，第二等词语用来表示名称，而并不表示任何特定的顺序。

Claims (10)

  1. 一种扫地机器人的控制方法，其中，所述方法包括：
    获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
    确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
    基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
  2. 根据权利要求1所述的方法，其中，所述确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径，包括：
    获取所述扫地机器人所处环境的初始地理环境信息；
    将所述初始地理环境信息在构建的全局环境地图中进行位置匹配，得到所述扫地机器人的初始位置，其中，所述全局环境地图由获取的全局地理环境信息构建得到。
    基于用户预设的虚拟墙信息和所述全局环境地图，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径。
  3. 根据权利要求1所述的方法，其中，所述实时信息包括：所述扫地机器人的实时地理环境信息和实时速度信息。
  4. 根据权利要求3所述的方法，其中，所述基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
    基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人按照所述全局无碰撞最佳路径进行移动时的无碰撞移动信 息；
    基于所述无碰撞移动信息和所述扫地机器人的移动模型，生成无碰撞移动控制信息；
    基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
  5. 根据权利要求4所述的方法，其中，所述基于所述清扫策略和所述无碰撞移动控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息，包括：
    基于获取的所述扫地机器人的实时地理环境信息和实时速度信息，确定所述扫地机器人在所述清扫任务中的清扫范围内，按照所述清扫策略进行移动时的无碰撞清扫信息；
    基于所述无碰撞清扫信息和所述扫地机器人的移动模型，生成无碰撞清扫控制信息；
    基于所述无碰撞移动控制信息和所述无碰撞清扫控制信息，确定所述扫地机器人执行所述清扫任务时的控制信息。
  6. 根据权利要求1所述的方法，其中，所述方法还包括：
    通过至少一个传感器获取所述扫地机器人的实时的定位数据信息，其中，所述定位数据信息包括每一个所述传感器实时采集的定位信息；
    对所述定位位置信息中的所有所述定位信息进行过滤，得到所述扫地机器人的有效定位数据信息；
    根据所述有效定位数据信息对所述扫地机器人进行实时定位。
  7. 根据权利要求6所述的方法，其中，所述传感器包括激光传感器、超 声传感器、红外传感器、摄像装置、深度传感器、里程计及防跌落传感器中的一项或多项。
  8. 根据权利要求1所述的方法，其中，所述方法还包括：
    对执行所述清扫任务时的所述控制信息进行更新。
  9. 一种基于计算的设备，其中，该设备包括：
    处理器；以及
    被安排成存储计算机可执行指令的存储器，所述可执行指令在被执行时使所述处理器：
    获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
    确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
    基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
  10. 一种存储可执行指令的非暂态计算机可读存储介质，在所述可执行指令由电子设备执行时，使得所述电子设备：
    获取清扫任务，其中，所述清扫任务包括清扫策略和清扫目的地；
    确定所述扫地机器人的初始位置，为所述扫地机器人规划出所述初始位置与所述清扫目的地之间的全局无碰撞最佳路径；
    基于获取的所述扫地机器人的实时信息、所述全局无碰撞最佳路径和所述清扫策略，确定所述扫地机器人执行所述清扫任务时的控制信息。
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Families Citing this family (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107450569A (zh) * 2017-09-27 2017-12-08 上海思岚科技有限公司 一种扫地机器人的控制方法及设备
CN109416251B (zh) * 2017-12-13 2020-01-07 广州艾若博机器人科技有限公司 基于色块标签的虚拟墙构建方法及装置、地图构建方法、可移动电子设备
CN108209745B (zh) * 2017-12-18 2021-06-25 深圳市奇虎智能科技有限公司 清洁设备的控制方法、装置、计算机设备和存储介质
JP2019109845A (ja) * 2017-12-20 2019-07-04 東芝ライフスタイル株式会社 自律型電気掃除機
CN108303980A (zh) * 2018-01-16 2018-07-20 上海木爷机器人技术有限公司 基于机器人实现虚拟墙图层的系统及方法
CN108398945A (zh) * 2018-01-17 2018-08-14 上海思岚科技有限公司 一种用于移动机器人执行任务的方法及设备
CN108196456A (zh) * 2018-01-22 2018-06-22 青岛海尔空调器有限总公司 一种智能家居感控方法、装置及空调
CN110169741B (zh) * 2018-06-25 2021-07-09 宁波洒哇地咔电器有限公司 一种清洁处理方法及设备
CN108628319B (zh) * 2018-07-04 2021-10-19 山东鹏耀智佳精密工业有限公司 一种扫地机器人智能避障系统
CN108784544B (zh) * 2018-07-16 2020-11-27 广州俊德信息科技有限公司 清洁电器的巡航清洁方法、系统、设备和可存储介质
CN108879882A (zh) * 2018-08-14 2018-11-23 河北彪悍运动器械有限公司 一种机器人自动充电的方法、装置及终端
CN109062217A (zh) * 2018-08-29 2018-12-21 广州市君望机器人自动化有限公司 对机器人十字路口的调度方法及装置
CN109358617A (zh) * 2018-09-25 2019-02-19 北京云迹科技有限公司 机器人定位方法、装置、机器人及终端设备
CN109407670B (zh) * 2018-12-07 2022-03-04 美智纵横科技有限责任公司 扫地机器人的距离探测方法及其装置和扫地机器人
CN111493746B (zh) * 2019-01-31 2023-07-04 北京奇虎科技有限公司 基于清洁机器人的清洁方法、装置、电子设备及存储介质
CN110209154B (zh) * 2019-04-09 2022-10-14 丰疆智能科技股份有限公司 自动收割机的残留收割路径规划系统及其方法
CN112525184A (zh) * 2019-08-28 2021-03-19 深圳拓邦股份有限公司 一种洗地机初始数据的获取方法、系统及洗地机
CN110916574B (zh) * 2019-10-18 2021-06-04 上海善解人意信息科技有限公司 扫地机器人系统及扫地机器人控制方法
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CN111839360B (zh) * 2020-06-22 2021-09-14 珠海格力电器股份有限公司 扫地机数据处理方法、装置、设备及计算机可读介质
CN113534812A (zh) * 2021-07-30 2021-10-22 上海高仙自动化科技发展有限公司 清洁机器人控制系统及清洁机器人

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090149990A1 (en) * 2007-12-11 2009-06-11 Samsung Electronics Co., Ltd. Method, medium, and apparatus for performing path planning of mobile robot
CN102138769A (zh) * 2010-01-28 2011-08-03 深圳先进技术研究院 清洁机器人及其清扫方法
CN102890507A (zh) * 2011-07-21 2013-01-23 鸿奇机器人股份有限公司 自走机器人、清洁机器人及其定位方法
CN104536447A (zh) * 2014-12-29 2015-04-22 重庆广建装饰股份有限公司 一种扫地机器人的导航方法
CN105320140A (zh) * 2015-12-01 2016-02-10 浙江宇视科技有限公司 一种扫地机器人及其清扫路径规划方法
CN105425801A (zh) * 2015-12-10 2016-03-23 长安大学 基于先进路径规划技术的智能清洁机器人及其清洁方法
CN105652870A (zh) * 2016-01-19 2016-06-08 中国人民解放军国防科学技术大学 一种智能安保服务机器人自主巡逻控制系统及自主巡逻控制方法
CN105739500A (zh) * 2016-03-29 2016-07-06 海尔优家智能科技（北京）有限公司 一种智能扫地机器人的交互控制方法及装置
CN106863305A (zh) * 2017-03-29 2017-06-20 赵博皓 一种扫地机器人房间地图创建方法及装置
CN107450569A (zh) * 2017-09-27 2017-12-08 上海思岚科技有限公司 一种扫地机器人的控制方法及设备

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104460663A (zh) * 2013-09-23 2015-03-25 科沃斯机器人科技(苏州)有限公司 智能手机控制清扫机器人的方法
CN105182978A (zh) * 2015-09-29 2015-12-23 江苏美的清洁电器股份有限公司 清扫装置、清扫系统和清扫方法
CN106227207A (zh) * 2016-07-29 2016-12-14 宇龙计算机通信科技(深圳)有限公司 智能清扫装置控制方法及系统
CN106239528B (zh) * 2016-08-30 2019-04-09 宁波菜鸟智能科技有限公司 扫地机器人的路径清扫方法
CN106444786B (zh) * 2016-11-29 2019-07-02 北京小米移动软件有限公司 扫地机器人的控制方法及装置和电子设备
CN106527446B (zh) * 2016-12-02 2020-11-13 北京小米移动软件有限公司 扫地机器人的控制方法及装置
CN206426107U (zh) * 2016-12-22 2017-08-22 武汉理工大学 家庭清洁机器人
CN107063242A (zh) * 2017-03-24 2017-08-18 上海思岚科技有限公司 具虚拟墙功能的定位导航装置和机器人
CN106843230B (zh) * 2017-03-24 2019-11-19 上海思岚科技有限公司 应用于移动设备的虚拟墙系统及其实现方法

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090149990A1 (en) * 2007-12-11 2009-06-11 Samsung Electronics Co., Ltd. Method, medium, and apparatus for performing path planning of mobile robot
CN102138769A (zh) * 2010-01-28 2011-08-03 深圳先进技术研究院 清洁机器人及其清扫方法
CN102890507A (zh) * 2011-07-21 2013-01-23 鸿奇机器人股份有限公司 自走机器人、清洁机器人及其定位方法
CN104536447A (zh) * 2014-12-29 2015-04-22 重庆广建装饰股份有限公司 一种扫地机器人的导航方法
CN105320140A (zh) * 2015-12-01 2016-02-10 浙江宇视科技有限公司 一种扫地机器人及其清扫路径规划方法
CN105425801A (zh) * 2015-12-10 2016-03-23 长安大学 基于先进路径规划技术的智能清洁机器人及其清洁方法
CN105652870A (zh) * 2016-01-19 2016-06-08 中国人民解放军国防科学技术大学 一种智能安保服务机器人自主巡逻控制系统及自主巡逻控制方法
CN105739500A (zh) * 2016-03-29 2016-07-06 海尔优家智能科技（北京）有限公司 一种智能扫地机器人的交互控制方法及装置
CN106863305A (zh) * 2017-03-29 2017-06-20 赵博皓 一种扫地机器人房间地图创建方法及装置
CN107450569A (zh) * 2017-09-27 2017-12-08 上海思岚科技有限公司 一种扫地机器人的控制方法及设备

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