WO2021103987A1 - Procédé de commande pour robot de balayage, robot de balayage et support de rangement - Google Patents

Procédé de commande pour robot de balayage, robot de balayage et support de rangement Download PDF

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Publication number
WO2021103987A1
WO2021103987A1 PCT/CN2020/127238 CN2020127238W WO2021103987A1 WO 2021103987 A1 WO2021103987 A1 WO 2021103987A1 CN 2020127238 W CN2020127238 W CN 2020127238W WO 2021103987 A1 WO2021103987 A1 WO 2021103987A1
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WO
WIPO (PCT)
Prior art keywords
obstacle
information
sweeping robot
category
automatic
Prior art date
Application number
PCT/CN2020/127238
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English (en)
Chinese (zh)
Inventor
杨勇
吴泽晓
Original Assignee
深圳市杉川机器人有限公司
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Publication of WO2021103987A1 publication Critical patent/WO2021103987A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/24—Floor-sweeping machines, motor-driven
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4061—Steering means; Means for avoiding obstacles; Details related to the place where the driver is accommodated
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection

Definitions

  • This application relates to the field of artificial intelligence technology, and in particular to an automatic control method of a sweeping robot, a sweeping robot, and a computer-readable storage medium.
  • an intelligent sweeping robot can automatically recognize obstacles and perform cleaning tasks on objects to be cleaned by avoiding obstacles, thereby reducing cleaning tasks for users.
  • obstacle avoidance is usually carried out by means of distance measurement, that is, obstacle avoidance by measuring the distance between the sweeping robot and the obstacle.
  • distance measurement that is, obstacle avoidance by measuring the distance between the sweeping robot and the obstacle.
  • the method based on distance measurement has the problem that the obstacle cannot be avoided more accurately.
  • the main purpose of this application is to provide an automatic control method for a sweeping robot, a sweeping robot, and a computer-readable storage medium, which aims to solve the problem of poor obstacle avoidance effects of the sweeping robot in the prior art.
  • the present application provides an automatic control method for a sweeping robot.
  • the method includes the following steps:
  • the sweeping robot is controlled to perform an automatic obstacle avoidance operation.
  • the step of controlling the sweeping robot to perform an automatic obstacle avoidance operation according to the obstacle category, position and depth information includes:
  • the sweeping robot is controlled not to perform the obstacle avoidance operation based on the position and depth information.
  • the step of controlling the sweeping robot to perform an automatic obstacle avoidance operation based on the position and depth information includes:
  • the step of controlling the sweeping robot to output alarm information after performing the automatic obstacle avoidance operation based on the position and depth information includes:
  • the sweeping robot After the sweeping robot performs the automatic obstacle avoidance operation, control the sweeping robot to output alarm information, and send the category and location of the second type of obstacle and the alarm information to the remote terminal;
  • control the cleaning robot If not received, control the cleaning robot to send alarm information to the remote terminal again until the processing information is received.
  • the step of controlling the sweeping robot not to perform the obstacle avoidance operation based on the position and depth information includes:
  • If the category of the obstacle is the third category, judge whether the sweeping robot needs to perform obstacle avoidance operations according to the power parameters and morphological parameters of the sweeping robot;
  • the sweeping robot is controlled not to perform obstacle avoidance operations based on the position and depth information.
  • the step of obtaining the category, position and depth information of the obstacle according to the image information of the obstacle includes:
  • a preset depth camera is used to identify obstacle position information and depth information in the image information.
  • the step of using an obstacle detection network to identify the category information and coordinate information of the obstacle in the image information includes:
  • the obstacle category identified by the obstacle detection network and the coordinate information of the obstacle detection frame are acquired.
  • the method further includes:
  • the present application also provides a cleaning robot including a memory, a processor, and a cleaning robot control method program stored on the processor and running on the processor.
  • a cleaning robot control method program stored on the processor and running on the processor.
  • the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a cleaning robot control method program, when the cleaning robot control method program is executed by a processor, the implementation is as described above. The steps of the sweeping robot control method described.
  • the obstacle category, position, and depth information are obtained according to the obstacle category, position, and depth information.
  • the depth information controls the sweeping robot to perform automatic obstacle avoidance operations. It can not only perform automatic obstacle avoidance operations, but also perform obstacle avoidance operations based on different obstacle categories. It can also perform more effective automatic obstacle avoidance operations based on the position and depth information of the obstacles, thereby improving the automatic obstacle avoidance of the sweeping robot. Efficiency and effectiveness.
  • FIG. 1 is a schematic structural diagram of a sweeping robot in a hardware operating environment involved in a solution of an embodiment of the application;
  • FIG. 2 is a schematic flowchart of a first embodiment of a method for controlling a cleaning robot according to the present application
  • FIG. 3 is a schematic flowchart of a second embodiment of a method for controlling a cleaning robot according to the present application
  • the sweeping robot is controlled to perform an automatic obstacle avoidance operation.
  • this application proposes a cleaning robot control method, a cleaning robot, and a computer-readable storage medium, which can obtain the category, position, and depth information of the obstacle by acquiring the image information of the obstacle during the travel of the cleaning robot.
  • the category, position and depth information of the object controls the sweeping robot to perform automatic obstacle avoidance operations, which can not only identify the obstacle category, but also perform automatic obstacle avoidance based on the position and depth information of the obstacle, which improves the automatic obstacle avoidance effect of the sweeping robot.
  • FIG. 1 is a schematic diagram of the structure of the sweeping robot in the hardware operating environment involved in the solution of the embodiment of the application.
  • the sweeping robot in the embodiment of the present application may be connected to terminal devices such as PCs, smart phones, and tablet computers, and the connection may be a wireless connection or a wired connection.
  • the cleaning robot may include: a communication bus 1002, a processor 1001, such as a CPU, a user interface 1003, a network interface 1004, and a memory 1005.
  • the communication bus 1002 is used to implement connection and communication between these components.
  • the user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).
  • the memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a magnetic disk memory.
  • the memory 1005 may also be a storage device independent of the aforementioned processor 1001.
  • the sweeping robot may further include a camera, an RF (Radio Frequency, radio frequency) circuit, a sensor, an audio circuit, a WiFi module, and so on.
  • sensors such as light sensors, motion sensors and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor.
  • the ambient light sensor can adjust the brightness of the display screen according to the brightness of the ambient light
  • the proximity sensor can turn off the display screen and/or when the mobile terminal is moved to the ear.
  • the gravity acceleration sensor can detect the magnitude of acceleration in various directions (usually three-axis), and can detect the magnitude and direction of gravity when it is stationary.
  • the mobile terminal can be used to identify the application of the mobile terminal's posture (such as horizontal and vertical screen switching, Related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, percussion), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, temperature sensor, etc. , I won’t repeat it here.
  • posture such as horizontal and vertical screen switching, Related games, magnetometer posture calibration
  • vibration recognition related functions such as pedometer, percussion
  • the mobile terminal can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, temperature sensor, etc. , I won’t repeat it here.
  • terminal structure shown in FIG. 1 does not constitute a limitation on the sweeping robot, and may include more or less components than shown in the figure, or combine certain components, or arrange different components.
  • a memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a cleaning robot control method program.
  • the network interface 1004 is mainly used to connect to the back-end server and communicate with the back-end server;
  • the user interface 1003 is mainly used to connect to the client (user side) and communicate with the client;
  • the device 1001 can be used to call the cleaning robot control method program stored in the memory 1005, and perform the following operations:
  • the sweeping robot is controlled to perform an automatic obstacle avoidance operation.
  • the processor 1001 may call the cleaning robot control method program stored in the memory 1005, and also perform the following operations:
  • the sweeping robot is controlled not to perform the obstacle avoidance operation based on the position and depth information.
  • the processor 1001 may call the cleaning robot control program stored in the memory 1005, and also perform the following operations:
  • the processor 1001 calls the cleaning robot control program stored in the memory 1005, and performs the following operations:
  • the sweeping robot After the sweeping robot performs the automatic obstacle avoidance operation, control the sweeping robot to output alarm information, and send the category and location of the second type of obstacle and the alarm information to the remote terminal;
  • control the cleaning robot If not received, control the cleaning robot to send alarm information to the remote terminal again until the processing information is received.
  • the processor 1001 may call the cleaning robot control program stored in the memory 1005, and also perform the following operations:
  • If the category of the obstacle is the third category, judge whether the sweeping robot needs to perform obstacle avoidance operations according to the power parameters and morphological parameters of the sweeping robot;
  • the sweeping robot is controlled not to perform obstacle avoidance operations based on the position and depth information.
  • the processor 1001 may call the cleaning robot control program stored in the memory 1005, and also perform the following operations: use an obstacle detection network to identify the category information and coordinate information of the obstacle in the image information;
  • a preset depth camera is used to identify obstacle position information and depth information in the image information.
  • the processor 1001 may call a control program of the sweeping robot stored in the memory 1005, and also perform the following operations: input the image information into the obstacle detection network, and determine whether the characteristic information of the obstacle extracted by the detection network is Match with the trained obstacle detection model;
  • the obstacle category identified by the obstacle detection network and the coordinate information of the obstacle detection frame are acquired.
  • the method further includes that the processor 1001 may call the sweeping robot control program stored in the memory 1005 , And also do the following:
  • Fig. 2 is a flowchart of a first embodiment of a cleaning robot control method according to the present application.
  • the cleaning robot control method includes the following steps:
  • Step S10 Obtain image information of obstacles during the traveling of the sweeping robot
  • the sweeping robot includes an image acquisition module, the image acquisition module includes a camera, the camera is used to collect real-time environmental image information of the surrounding environment of the sweeping robot in the process of traveling, and the sweeping robot is obtained by judging whether there are obstacles in the environmental image information Image information of obstacles in the process of traveling.
  • the method of judging whether there are obstacles in the environmental image information can use image recognition technology similar to face recognition.
  • the obstacle detection network By training the obstacle detection network, the collected environmental image information is input into the trained obstacle detection network.
  • feature extraction is performed on the collected environmental image information, if the extracted feature information can match the trained obstacle detection model, then there are obstacles in the collected environmental image information. If the extracted feature information can match the trained obstacle detection model If the network matches, there are no obstacles in the collected environmental image information. After judging whether there are obstacles in the collected environmental image information, if so, obtain the image information of the obstacles as the image information of the obstacles in the process of the sweeping robot during the travel, and further identify the obstacles through the trained obstacle detection network The category and other related
  • Step S20 Obtain the category, position and depth information of the obstacle according to the image information of the obstacle;
  • the obstacle detection network After obtaining the image information of the obstacle, the obstacle detection network is used to identify the category information and coordinate information of the obstacle in the image information, and based on the coordinate information, the preset depth camera is used to identify the obstacle position information and the obstacle position information in the image information. In-depth information. Specifically, the image information of the obstacle is input into the obstacle detection network, and when it is determined that there is an obstacle in the image information collected by the camera, the obstacle category information and the obstacle detection frame recognized by the obstacle detection network are obtained. The coordinate information. Before judging whether there are obstacles in the image information collected by the camera, it is necessary to train the obstacle detection network.
  • the specific training process is as follows: Collect a large number of pictures of obstacles that need to be avoided (for example: 10,000), Use the segmentation tool to show the outline of the obstacle that needs to be labeled to obtain the labeled image, and save it as a corresponding json format file after labeling. Generate the coordinate information of the four vertices of the corresponding detection frame and the obstacle category information in the annotated image in the saved json format file for the annotated image. In the labeling process, the labeling is increased in order from the time when the object category is 0, until all the recognition categories are labeled.
  • the json format file is converted into an xml format file for training the obstacle detection network, and finally converted into a record file that the obstacle network model can recognize and train.
  • the converted file is sent to the obstacle detection model for training and the parameters are configured, and the number of training steps is set according to the number of pictures.
  • the training is stopped. Convert the trained name into a file that can be used for obstacle detection.
  • the training process of the obstacle detection network is essentially a feature extraction process. After the features are extracted, the network is continuously predicted.
  • the predicted value is compared with the real value to optimize the parameters, and finally the ability to accurately predict the object and location information is realized.
  • the obstacle detection network After the obstacle detection network is trained, the real-time collected image data is input to the obstacle detection network.
  • the obstacle detection network extracts obstacle features in the data image to output information such as object category, vertex coordinates of the detection frame, and confidence. When the confidence level exceeds the preset confidence level, it can be judged that there is an obstacle in the image information collected in real time. When there is an obstacle, the coordinate information and category information of the detection frame corresponding to the obstacle are output through the obstacle detection network.
  • the preset depth camera can be TOF (Time of flight, flight time) camera, it can also be a binocular stereo camera, or a monocular structured light camera and other depth cameras that can obtain object depth information.
  • TOF Time of flight, flight time
  • the preset depth camera can also be a binocular stereo camera, or a monocular structured light camera and other depth cameras that can obtain object depth information.
  • ToF Time of flight, flight time
  • the way to send light pulses to scan to obtain depth information can be point scanning, point-by-point scanning to obtain the three-dimensional geometric structure of the target, or surface scanning, which can be real-time by taking a picture of the scene Obtain the surface geometry information of the entire scene.
  • the method of surface scanning may be adopted. First, a scene image is collected, and the scene image is sent to the detection network for detection. When there are obstacles in the scene image, the detection information output by the detection network is used. TOF (Time of flight, flight time) The camera further obtains the depth information of the obstacle.
  • Step S30 Control the sweeping robot to perform an automatic obstacle avoidance operation according to the obstacle category, position and depth information;
  • the sweeping robot is controlled to automatically perform corresponding obstacle avoidance operations.
  • the obstacle is an unavoidable obstacle, re-plan the cleaning route and do not perform automatic obstacle avoidance operation; when the obstacle is an obstacle avoidable type, it can be further judged whether the obstacle is The obstacle that needs to be cleaned, if it is an obstacle that needs to be cleaned, it will directly perform the cleaning operation without automatic obstacle avoidance operation, if it is an obstacle that needs to be cleaned, it will judge whether the sweeping robot can clean autonomously, if it can clean autonomously, then Control the sweeping robot to clean autonomously. If it cannot clean, it will control the sweeping robot to receive the cleaning instruction sent by the terminal device to clean.
  • the corresponding obstacle avoidance route can be planned for the sweeping robot according to the position and depth information corresponding to the obstacle category.
  • the planning of obstacle avoidance routes can be based on obstacle avoidance safety, obstacle avoidance time, obstacle avoidance routes, etc., and one of the planned obstacle avoidance routes can be selected to ensure the safety factor of obstacle avoidance and ensure the avoidance of obstacles. After the obstacle is cleared, follow the original cleaning trajectory and the obstacle avoidance route with the shortest turning time when avoiding the obstacle.
  • multiple planned obstacle avoidance routes can also be sent to the terminal device, and after the terminal device specifies the corresponding obstacle avoidance route, the sweeping robot is controlled to perform the obstacle avoidance operation according to the obstacle avoidance route specified by the user on the terminal device side.
  • Obstacle avoidance operations can perform corresponding automatic obstacle avoidance operations for different types of obstacles, and perform automatic obstacle avoidance operations for obstacles with different position and depth information, so as to improve the accuracy of automatic obstacle avoidance and improve automatic avoidance. The efficiency and effectiveness of barriers.
  • Fig. 3 is a flowchart of a second embodiment of a cleaning robot control method according to the present application.
  • the cleaning robot control method includes the following steps:
  • Step S11 Obtain image information of obstacles during the traveling of the sweeping robot
  • Step S12 Obtain the category, position and depth information of the obstacle according to the image information of the obstacle;
  • Step S13 If the category of the obstacle is the first category, control the sweeping robot to perform an automatic obstacle avoidance operation based on the position and depth information;
  • Step S14 if the category of the obstacle is the second category, based on the position and depth information, control the sweeping robot to output alarm information after performing the automatic obstacle avoidance operation;
  • Step S15 If the category of the obstacle is the third category, control the sweeping robot not to perform obstacle avoidance operations based on the position and depth information.
  • the category, position, and depth information of the obstacle are acquired according to the image information of the obstacle.
  • the types of obstacles when the obstacles are of different types, based on different types of obstacles, different obstacle avoidance operations are performed based on the location and depth information of the obstacles. Therefore, before performing different obstacle avoidance operations based on different types of obstacles, it is necessary to classify the obstacles.
  • the classification method can be based on whether the obstacle is an obstacle that needs to be avoided, whether it is an obstacle that can be avoided, whether it is an obstacle that needs to be cleaned, whether it is an obstacle that can be cleaned by a sweeping robot, etc., as classification conditions, Classify obstacles.
  • a better classification method takes the obstacles that the robot sweeping needs to avoid and can avoid obstacles as the first type of obstacles, and the obstacles that the sweeping robot needs to avoid obstacles and need to be cleaned but cannot be cleaned by the sweeping robot are regarded as the first type of obstacles. Obstacles of the second type, the obstacles that the sweeping robot does not need to avoid obstacles but need to be cleaned and can be cleaned are regarded as the third type of obstacles.
  • the steering distance information, steering direction information, and steering angle information of the sweeping robot are determined according to the position and depth information of the obstacle; according to the sweeping robot
  • the robot steering distance information, steering direction information, and steering angle information determine the obstacle avoidance route; the sweeping robot is controlled to perform automatic obstacle avoidance operations according to the obstacle avoidance route.
  • the shortest distance of the obstacle relative to the front of the sweeping robot is determined to determine the steering distance information.
  • the robot has completed the cleaning of the left and right areas to determine the steering direction information. According to the position and depth information of the obstacle, it will be able to effectively avoid the obstacle and continue to clean along the cleaning route specified by the original cleaning task to determine the best obstacle avoidance angle to determine the steering Angle information.
  • the obstacle avoidance route can be planned based on these information, so as to control the sweeping robot to perform automatic obstacle avoidance operations on the planned obstacle avoidance route; if the obstacle category is the first In the second category, the sweeping robot is controlled to perform automatic obstacle avoidance operations based on the position and depth information; after the sweeping robot performs the obstacle avoidance operation, because the second category of obstacles cannot be cleaned, the user on the terminal device side needs to be notified to come To process. At this time, after the sweeping robot performs the automatic obstacle avoidance operation, the sweeping robot is controlled to output alarm information.
  • the alarm information is output, there are two ways: the first is the way that the sweeping robot outputs in the form of audio through its own alarm , The second way is to output the alarm information to the terminal device. Of course, it can also be a combination of the two methods.
  • the category and location of the second type of obstacle and the alarm information are sent to the terminal; by recording the time when the sweeping robot sends the alarm information, Determine whether the processing information sent by the terminal is received within the preset time corresponding to the category and location information; if not, control the sweeping robot to send alarm information to the terminal again, and stop sending the alarm until the processing information is received information.
  • the sweeping robot is controlled not to perform the obstacle avoidance operation based on the position and depth information.
  • the morphological parameters of the sweeping robot such as height, whether it has supporting feet for lifting, etc.
  • the sweeping robot After the sweeping robot has worked for a period of time, judge whether the sweeping robot can step over the current obstacle under the current power parameters according to the power parameters of the sweeping robot (such as remaining power, output power, etc.), and continue to perform the cleaning route performed by the original cleaning task Clean up.
  • the power parameters of the sweeping robot such as remaining power, output power, etc.
  • the category, position, and depth information of the obstacle are acquired according to the image information of the obstacle. If the category of the obstacle is the first type, it is based on The position and depth information controls the sweeping robot to perform automatic obstacle avoidance operations. If the category of the obstacle is the second type, the sweeping robot is controlled based on the position and depth information to output alarm information after performing the automatic obstacle avoidance operation, if If the category of the obstacle is the third category, based on the position and depth information, the sweeping robot is controlled not to perform obstacle avoidance operations. For different types of obstacles, perform corresponding automatic obstacle avoidance operations according to their position and depth information. , It can not only prevent missed scanning, but also alarm and notify the terminal user to deal with it, which can effectively improve the efficiency of obstacle avoidance.
  • an embodiment of the present application also provides a cleaning robot.
  • the cleaning robot includes a memory, a processor, and a cleaning robot control program stored on the processor and running on the processor, and the processor executes the The cleaning robot control program implements the steps of the cleaning robot control method as described above.
  • an embodiment of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a cleaning robot control program, and the cleaning robot control program is executed by a processor to realize the above-mentioned cleaning robot control Method steps.

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Abstract

L'invention concerne un procédé de commande automatique pour un robot de balayage. Le procédé comprend les étapes suivantes consistant à : obtenir des informations d'image d'un obstacle au cours du déplacement d'un robot de balayage; obtenir les informations de catégorie, de position et de profondeur de l'obstacle en fonction des informations d'image de l'obstacle; et en fonction des informations de catégorie, de position et de profondeur de l'obstacle, commander le robot de balayage pour effectuer une opération d'évitement d'obstacle automatique.
PCT/CN2020/127238 2019-11-29 2020-11-06 Procédé de commande pour robot de balayage, robot de balayage et support de rangement WO2021103987A1 (fr)

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CN201911212870.4 2019-11-29
CN201911212870.4A CN110974088B (zh) 2019-11-29 2019-11-29 扫地机器人控制方法、扫地机器人及存储介质

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