CN111067440A

CN111067440A - Cleaning robot control method and cleaning robot

Info

Publication number: CN111067440A
Application number: CN201911426179.6A
Authority: CN
Inventors: 龚凯
Original assignee: Shenzhen Feike Robot Co ltd
Current assignee: Shenzhen Feike Robot Co ltd
Priority date: 2019-12-31
Filing date: 2019-12-31
Publication date: 2020-04-28

Abstract

The application provides a cleaning robot control method and a cleaning robot, wherein the cleaning robot comprises a main body, a controller and an image acquisition device; wherein: the image acquisition device is used for acquiring images of obstacles in the operating environment of the cleaning robot; the controller is used for identifying the type of the obstacle according to the image of the obstacle; the method is also used for determining the distance between the barriers along the wall corresponding to the type of the barrier, wherein different barrier types correspond to different distances between the barriers along the wall; and the controller controls the cleaning robot to move along the wall along the boundary of the obstacle according to the distance along the wall corresponding to the type of the obstacle. By implementing the method and the device, the cleaning coverage rate can be improved in the wall walking process aiming at different obstacles, and the cleaning risk is reduced.

Description

Cleaning robot control method and cleaning robot

Technical Field

The invention relates to the field of intelligent robots, in particular to a cleaning robot control method and a cleaning robot.

Background

In modern life, cleaning robots are increasingly used and popularized. During the cleaning process of the cleaning robot, various obstacles can be encountered, such as walls, tables, chairs, vases and the like. The existing obstacle processing scheme is mainly that a non-contact sensor, such as an infrared, laser or ultrasonic distance measuring sensor and the like, is arranged at the front part or the top part of a cleaning robot, and the robot walks along a wall by measuring the distance between the robot and an obstacle. In the prior art, when a cleaning robot encounters an obstacle in the cleaning process, the cleaning robot adopts a fixed interval to carry out wall following, so that some obstacle regions possibly miss too many, some obstacle regions can damage the obstacle, and the like, and therefore, how to control the wall following movement of the cleaning robot when the cleaning robot faces the obstacle is important.

Disclosure of Invention

The embodiment of the application provides a cleaning robot control method and a cleaning robot, which can realize different wall-following motions aiming at different obstacles, improve the cleaning coverage rate in the wall-following motion process and reduce the cleaning risk.

In a first aspect, embodiments of the present application provide a cleaning robot control method applied to a cleaning robot including a body and a sweeping device extending beyond an edge of the body and for sweeping a floor area outside the edge of the body. The method comprises the following steps: acquiring an image of an obstacle in an operating environment of the cleaning robot; identifying the type of the obstacle according to the image of the obstacle; determining the distance between the barriers along the wall corresponding to the type of the barrier, wherein different barrier types correspond to different distances between the barriers along the wall; and controlling the cleaning robot to move along the wall along the boundary of the obstacle according to the distance along the wall corresponding to the type of the obstacle.

It can be seen that, implement this application embodiment, cleaning machines people can distinguish the barrier of different grade type in the environment, according to different barrier types, adopt different along the wall interval to get into along the wall mode, consequently, can reach more excellent along the wall route, avoid the robot to be absorbed in and threaten the border or contact the article that can not contact, like this, can realize different obstacle-avoiding distance to different barriers, ensure that the barrier of should keeping away from just keeps away from, the barrier that should be close to as far as possible then is close to as far as possible, thereby can greatly promote and clean the coverage, simultaneously, the very big degree reduces the risk or the negative effects of barrier and/or cleaning machines people, improves and cleans the security.

The obstacle type is determined through the image detection method, the influence of the color of the obstacle is small, the obstacle avoidance distance is not different due to different colors of the obstacle, and the defects of the prior art are avoided.

Based on the first aspect, in a possible embodiment, after the determining the distance along the wall corresponding to the type of the obstacle, the method further includes: obtaining the reliability of the boundary of the obstacle, wherein the reliability of the boundary of the obstacle and the distance between the obstacle and the wall form an inverse correlation relationship; correcting the wall-following distance corresponding to the type of the obstacle according to the reliability of the obstacle boundary to obtain the corrected wall-following distance;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps: and controlling the cleaning robot to move along the wall along the barrier boundary according to the corrected distance along the wall.

That is to say, the embodiment of the application can comprehensively consider the influence of the boundary confidence level on the basis of considering the types of the obstacles and correct the distance along the wall, so that the planned path along the wall is better, the path along the wall has higher accuracy and practical operability, the cleaning coverage rate is favorably improved to the highest, and meanwhile, the risk or negative influence is controlled to the lowest.

Based on the first aspect, in a possible embodiment, after the determining the distance along the wall corresponding to the type of the obstacle, the method further includes: acquiring the movement speed of the cleaning robot, wherein the movement speed of the robot is in positive correlation with the distance between the obstacles along the wall; correcting the wall-following distance of the barrier according to the movement speed of the cleaning robot to obtain the corrected wall-following distance;

That is to say, this application embodiment still can be on the basis of considering the barrier type again the comprehensive consideration cleaning robot's the influence of moving speed, revise along the wall interval, therefore the planned is better along the wall route, and along the wall route more have higher accuracy and practical maneuverability, be favorable to promoting to the highest with cleaning coverage, simultaneously, with risk or negative effects control to minimumly.

Based on the first aspect, in a possible embodiment, the identifying the type of the obstacle from the image of the obstacle includes: identifying a type of the obstacle as one of: non-dangerous type obstacles; a dangerous type of obstacle.

When the type of the obstacle represents a non-dangerous obstacle, the wall-following distance is a first wall-following distance;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps: controlling the cleaning robot to perform a wall-following motion along the obstacle boundary based on the first wall-following distance;

when the type of the obstacle represents a dangerous obstacle, the distance between every two adjacent walls is a second distance between every two adjacent walls;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps: controlling the cleaning robot to perform a wall-following motion along the obstacle boundary based on the second wall-following distance;

wherein the second inter-wall spacing is greater than the first inter-wall spacing, the first inter-wall spacing causing the sweeping device to contact the obstacle boundary; the second wall-wise spacing is such that the sweeping device cannot contact the obstacle boundary.

Therefore, different obstacle avoidance distances can be realized for different obstacles, the obstacles (such as dangerous obstacles) which are not close to each other are ensured not to be close to each other, the obstacles (such as non-dangerous obstacles) which are close to each other as much as possible are close to each other, the cleaning coverage rate can be greatly improved, meanwhile, the risks or negative influences of the obstacles and/or the cleaning robot are greatly reduced, and the cleaning safety is improved.

Based on the first aspect, in a possible embodiment, the dangerous type obstacle includes at least one of: dangerously inaccessible to the barrier-like object; the high risk requires a distance from the obstacle.

When the type of the obstacle indicates that a danger cannot approach the obstacle, the wall-following distance is a third wall-following distance;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps: controlling the cleaning robot to perform a wall-following motion along the obstacle boundary based on the third wall-following distance;

when the type of the obstacle indicates that high risk needs to be kept away from the obstacle, the distance between the two walls is a fourth distance between the two walls;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps: controlling the cleaning robot to perform a wall-following motion along the obstacle boundary based on the fourth wall-following pitch;

wherein the fourth wall-following distance is greater than the third wall-following distance.

Therefore, different obstacle avoidance distances can be realized for different obstacles, the distance that the obstacle is far away from when the high-risk obstacle needs to be far away is larger than the distance that the obstacle is far away from when the high-risk obstacle needs to be far away, the obstacle avoidance distances are designed differently according to the different obstacle danger degrees, the cleaning coverage rate can be improved, meanwhile, the risk or negative influence of the obstacle and/or the cleaning robot is reduced in a targeted mode, and the cleaning safety is improved.

Based on the first aspect, in a possible embodiment, before controlling the cleaning robot to perform the wall-following movement along the obstacle boundary according to the wall-following distance corresponding to the type of the obstacle, the method further includes:

determining an action starting point in the advancing direction of the cleaning robot, wherein the distance between the action starting point and the barrier boundary is larger than the distance between the barrier boundaries along the wall; and controlling the cleaning robot to decelerate from the position of the action starting point, so that the reserved distance and the obstacle avoidance time are used as buffer, and the following wall following path can be realized better.

For example, for some obstacle types that can be approached by the cleaning robot, the motion starting point distance may be shorter or the deceleration acceleration may be smaller. For example, the obstacle is a bedside, the cleaning robot can start to move at a short movement starting point distance, so that the cleaning robot can be close to the obstacle as much as possible, and the cleaning coverage rate is improved as much as possible.

Based on the first aspect, in a possible embodiment, the distance along the wall can be such that the distance between the main body of the cleaning robot and the obstacle satisfies a preset condition (the distance may be referred to as a first distance) and the distance between the side sweep of the cleaning robot and the obstacle satisfies a further preset condition (the distance may be referred to as a second distance) when entering the path along the wall.

According to the first aspect, in a possible embodiment, the body is telescopically connected with the sweeping device; before controlling the cleaning robot to move along the wall along the barrier boundary according to the distance along the wall corresponding to the type of the barrier, the method further comprises the following steps:

and when the machine body reaches the first distance, controlling the cleaning device to stretch relative to the machine body so as to enable the cleaning device to reach the second distance.

Based on the first aspect, in a possible embodiment, before the moving and cleaning along the wall path, the method further includes: calculating to obtain an obstacle boundary according to the image of the obstacle; calculating a third distance from the obstacle boundary to the fuselage main body according to the image of the obstacle; calibrating the obstacle boundary on a SLAM map according to the third distance; performing path planning according to the SLAM map with the marked obstacle boundary and the wall-following path to obtain a global motion path;

correspondingly, the moving and cleaning according to the path along the wall includes: and moving and cleaning according to the global motion path.

It can be seen that the cleaning robot in the embodiment of the application can distinguish different types of obstacles in the environment through image detection or obstacle boundaries stored on the SLAM map, determine different wall-following distances according to different obstacle types, thereby obtaining different wall-following paths, calibrate the obstacle boundaries into the SLAM map, and perform comprehensive route planning by combining the SLAM map and the wall-following paths. Like this, can enough realize different along the wall interval to different barriers to with clean the coverage and promote the highest while with risk or negative effects control to minimumly, can also have more abundant distance to formulate global movement path, consequently along the wall route can be more reasonable, more have actual maneuverability.

Based on the first aspect, in a possible embodiment, when the cleaning robot adjusts the direction of the original movement path to enter the along-the-wall path, if the housing of the cleaning robot is circular, the cleaning robot can turn around concentrically based on the wheel device, and if the housing of the cleaning robot is non-circular, the cleaning robot can further adjust the distance when adjusting the direction according to whether the cleaning robot will hit an obstacle when adjusting the direction in addition to turning around based on the wheel device.

In a second aspect, an embodiment of the present application provides a cleaning robot, including a main body and a cleaning device connected to the main body, where the main body includes a controller and an image acquisition device; the sweeping device extends beyond the edge of the fuselage body and is used to sweep an area of the ground beyond the edge of the fuselage body. Wherein: the image acquisition device is used for acquiring images of obstacles in the operating environment of the cleaning robot; the controller is used for identifying the type of the obstacle according to the image of the obstacle; the obstacle detection device is also used for determining the distance between the walls corresponding to the type of the obstacle, wherein different obstacle types correspond to different distances between the walls; the controller is used for controlling the cleaning robot to move along the wall along the barrier boundary according to the distance along the wall corresponding to the type of the barrier.

The various components of the cleaning robot may be used in particular to implement the method described in the first aspect.

In a third aspect, embodiments of the present application provide a non-volatile storage medium for storing program instructions that, when applied to a cleaning robot, may be used to implement the method described in the first aspect.

In a fourth aspect, embodiments of the present application provide a computer program product; the computer program product comprising program instructions which, when executed by a cleaning robot, cause the cleaning robot to perform the method of the first aspect as described above. The computer program product may be a software installation package, which, in case it is desired to use the method provided by any of the possible designs of the first aspect described above, may be downloaded and executed on a cleaning robot for carrying out the method of the first aspect.

It can be seen that, by implementing the embodiment of the application, the cleaning robot can distinguish different types of obstacles in the environment, and adopts different wall-following intervals to enter a wall-following mode according to different obstacle types, so that a better wall-following path can be achieved, the robot is prevented from being trapped in a threat or contacting objects (such as animal wastes) which cannot be contacted, different obstacle avoiding distances can be realized aiming at different obstacles, the far-away obstacles (such as high-risk obstacles) are ensured to be far away, the obstacles (such as non-risk obstacles) which are as close as possible are close as possible, the cleaning coverage rate can be greatly improved, meanwhile, the risks or negative influences of the obstacles and/or the cleaning robot are greatly reduced, and the cleaning safety is improved. In addition, the method and the device can comprehensively consider the influence of factors such as the boundary confidence level and the moving speed of the cleaning robot on the basis of considering the type of the obstacle and correct the distance between the two walls, so that the planned path along the wall is better, the path along the wall has higher accuracy and practical operability, the cleaning coverage rate is improved to the highest degree, and meanwhile, the risk or negative influence is controlled to the lowest degree. In addition, the embodiment of the application is less affected by the colors of the obstacles, so that the obstacle avoidance distances are not the same due to different colors of the obstacles, and the defects of the prior art are avoided.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1A is a schematic top view of a cleaning robot provided in an exemplary embodiment of the present application;

fig. 1B is a schematic bottom view of a cleaning robot provided in an exemplary embodiment of the present disclosure;

FIG. 2 is a schematic structural diagram of a cleaning robot provided in an exemplary embodiment of the present disclosure;

fig. 3 is a functional structure diagram of a controller of a cleaning robot according to an exemplary embodiment of the present disclosure;

fig. 4 is a schematic flowchart of a control method of a cleaning robot according to an embodiment of the present disclosure;

fig. 5 is a schematic diagram of a cleaning robot based on a wall path along an obstacle boundary in an application scenario according to an embodiment of the present application;

fig. 6 is a schematic diagram of a distance along a wall of a cleaning robot in an application scenario according to an embodiment of the present application;

FIG. 7 is a schematic diagram of a distance along a wall of a cleaning robot in another application scenario provided by an embodiment of the present application;

FIG. 8 is a schematic flow chart illustrating a further method for controlling a cleaning robot according to an embodiment of the present disclosure;

fig. 9 is a schematic view of a global motion path of a cleaning robot in an application scenario according to an embodiment of the present application;

fig. 10 is a schematic view of a global motion path of a cleaning robot in another application scenario provided in an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It is to be understood that the terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only, and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

Fig. 1A and 1B are schematic structural diagrams of a cleaning robot 10 according to an embodiment of the present disclosure, in which fig. 1A shows a top view of the cleaning robot 10, and fig. 1B shows a bottom view of the cleaning robot 10. As shown in fig. 1A and 1B, the cleaning robot 10 includes: a main body 101 and a cleaning device connected to the main body 101, wherein the cleaning device may include one or more edge brushes (e.g., edge brush 1021 and edge brush 1022). In some embodiments, the sweeping device may also include one or more main sweeps 1041. The main body 101 includes a housing of the cleaning robot, and various components accommodated in the housing.

The wheel arrangement may be partially housed in the housing (the wheel arrangement is also referred to herein as a wheel arrangement, and as illustrated the wheel arrangement includes a drive wheel 1031, a drive wheel 1032, and a driven wheel 1033). One of the

driving wheels

1031 and 1032 is a left driving wheel, and the other is a right driving wheel. The

drive wheels

1031 and 1032 are respectively arranged centrally in a symmetrical manner on opposite sides of the bottom of the machine body 101. The moving operation including the forward movement, the backward movement, and the rotation is performed during the cleaning. A driven wheel 1033 is provided at a front portion of the machine body 101 for changing a traveling direction of the cleaning robot during traveling.

An image capture device (such as a camera 1051 in the illustration) is disposed on the housing. Optionally, one or more sensors (including a contact sensor 1061 as shown) are also provided on the housing.

In one embodiment, the housing of the cleaning robot 10 may be circular, or may be other shapes (such as square, oval, etc.), and is not limited herein.

In a specific implementation, the image capturing device may be a monocular camera or a binocular camera, and is disposed in a front position above the housing of the main body of the robot body, and is configured to capture or record images of obstacles encountered by the cleaning robot in a traveling direction, and transmit the images or videos to related components accommodated in the housing, and the related components implement route planning of the cleaning robot 10 based on the images or videos. The related components contained in the housing can refer to the description of the embodiment in fig. 2, and are not described again here.

In some embodiments, in addition to the front camera, a camera may be installed at other positions, such as the rear portion and the bottom portion of the main body, for capturing an environmental image of the periphery of the main body and storing the captured environmental image in the memory 315.

In a specific implementation, the wheel device may be fixedly connected with the housing, and the wheel device is used for performing movement based on driving of relevant components of the main body of the fuselage, and specifically, may be used for forward movement, backward movement, movement direction adjustment and the like, and for acceleration, deceleration, uniform speed, pause and the like. For example, as shown in fig. 1B, the driving

wheels

1031 and 1032 can be used for forward or backward movement, and the driven wheels 1033 can be used for adjusting the moving direction. The

driver

1031 and 1032 can also be used to realize acceleration, deceleration, uniform speed, pause, etc. It should be noted that the present application is not limited to the specific location of the wheel assembly below the housing.

In one implementation, a side sweep may be provided at a forward location beneath the housing for garbage sweeping while the cleaning robot 10 is traveling. For example, as shown in fig. 1B, the side sweep includes a side sweep 1021 and a side sweep 1022, and both the side sweep 1021 and the side sweep 1022 protrude a certain relative distance from the front of the housing, so as to expand the cleaning range and implement the cleaning robot control method described in the embodiment of the present application. In one example, the edge wiper may be fixedly attached to the housing, wherein the edge of the edge wiper is fixed relative to the housing. In another example, the edge sweeper can be telescopically coupled to the housing, wherein the distance between the edge of the edge sweeper and the housing can be changed, i.e., the sweeping distance (range) can be changed by telescoping.

In one embodiment, the main sweeper 1041 may be disposed at the bottom of the housing for further sweeping and recycling the garbage swept by the side sweeper during the traveling of the cleaning robot 10. For example, as shown in fig. 1B, the main broom 1041 may be a drum-shaped rotating brush rotating in a roller shape, and a garbage collection chamber (not shown) is further provided inside the housing, and is engaged with the main broom 1041 for collecting the garbage collected by the main broom 1041.

It should be noted that, in practical applications, the cleaning robot 10 may further include other modules or components, for example, the cleaning robot 10 further includes a recharging stand for implementing an autonomous intelligent charging of the cleaning robot 10, and the embodiment of the present invention is not limited thereto.

Referring to fig. 2, fig. 2 is a block diagram of a specific implementation manner of the cleaning robot 10 according to the embodiment of the present disclosure. As shown in fig. 2, the cleaning robot 10 may include: chip 310, memory 315 (one or more computer-readable storage media), peripheral system 317. These components may communicate over one or more communication buses 314.

The peripheral system 317 is mainly used for implementing an interaction function between the SLAM terminal 300 and a user/external environment, and in specific implementation, the peripheral system 317 may include: a motion management module 318, a camera management module 319, a cleaning management module 320, and a sensor management module 321. Wherein each management module can be coupled to its respective peripheral device, such as wheel assembly 323, camera 324, sweeping assembly 325, sensor 326, etc. Wherein:

in some embodiments, wheel assembly 323 may further include a drive wheel and a driven wheel, the functions of which may be referenced above.

In some embodiments, camera 324 may be a monocular or binocular camera or a depth camera.

In some embodiments, the sweeping device 325 may include, for example, side sweeps and main sweeps, the functions of which may be referred to above.

In some alternative embodiments, the sensors 326 may further include one or more of the following sensors: a contact sensor for detecting whether the cleaning robot 10 is in contact with an obstacle, which may further include a switch, a capacitance sensor, a pressure sensor, etc.; a speedometer for detecting a traveling speed of the cleaning robot 10; an accelerometer for detecting acceleration of the cleaning robot 10; and an odometer for detecting a driving mileage of the cleaning robot 10. In some embodiments, sensors 326 also include infrared sensors, ultrasonic sensors, Radio Frequency (RF) sensors, geomagnetic sensors, Position Sensitive Device (PSD) sensors, and the like. The sensor 326 is used to sense obstacle data around the cleaning robot.

It should be noted that the peripheral system 317 may also include other I/O peripherals, which are not limited herein.

Chip 310 may be integrated including: one or more controllers 311, a clock module 312, and possibly a power management module 313. The clock module 312 integrated in the chip 310 is mainly used for generating clocks required for data transmission and timing control for the controller 311. The power management module 313 integrated in the baseband chip 310 is mainly used to provide stable and high-precision voltage for the controller 311 and peripheral systems. Controller 311 includes, but is not limited to: a central processing unit, a singlechip, a digital signal processor, a microprocessor and the like.

The memory 315 is coupled to the controller 311 for storing various data (e.g., obstacle types, mapping between obstacle types and along-wall distances), various software programs and/or sets of program instructions, a map of the travel area of the cleaning robot 10. In particular implementations, memory 315 may include high speed random access memory and may also include non-volatile memory. Such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. The memory 315 may also store one or more application programs, such as a SLAM system program, a deep learning image algorithm, a route planning algorithm, and the like.

In some embodiments, the map includes a global location map, locations of various rooms in the travel area, location information for obstacles, types of obstacles, and the like. The data in the map is updated based on data sensed by various sensors during the travel of the cleaning robot 10.

It should be understood that the cleaning robot 10 may have more or fewer components than shown in fig. 2, may combine two or more components, or may have a different configuration implementation of components in a particular application scenario.

In this embodiment of the application, the controller 311 may be configured to call program instructions and data in a memory to implement a cleaning robot control method described below, which is not described herein for brevity of the description.

The relevant functional blocks of the controller 311 are described further below. Referring to fig. 3, fig. 3 is a block diagram of a specific implementation of the controller 311, and as shown in fig. 3, the controller 311 further includes an image acquisition module 401, a wall motion module 403, an image distance measurement module 405, a wall motion module 407, and a SLAM module 409 (or SLAM system), where:

and an image obtaining module 401, configured to obtain an image of the obstacle collected by the camera. In a specific implementation, the image obtaining module 401 may be used to perform step 201 described later.

A wall-following motion module 403 for determining the type of the obstacle according to the image of the obstacle; and the method is also used for calculating the boundary of the obstacle according to the image of the obstacle. In particular implementations, the along-the-wall motion module 403 may be used, for example, to perform step 202 below.

And the image ranging module 405 is configured to calculate a distance from the obstacle to the main body of the fuselage according to the image of the obstacle.

And the obstacle processing module 407 is configured to determine a distance along the wall corresponding to the type of the obstacle. In a specific implementation, the obstacle handling module 407 may be configured to perform the following step 203, for example.

In some embodiments, the distance along the wall may enable the cleaning robot to enter the wall-following mode, a distance between the main body of the cleaning robot and the obstacle satisfying a first preset condition (the distance satisfying the first preset condition may be referred to as a first distance), and a distance between the side broom of the cleaning robot and the obstacle satisfying a second preset condition (the distance satisfying the second preset condition may be referred to as a second distance). Thus, the first distance is used to indicate a distance between the body and the obstacle when entering the wall-following path, and the second distance is used to indicate a distance between the side-sweep and the obstacle when entering the wall-following path.

And the map processing module 409 is configured to calibrate the obstacle boundary in an SLAM map according to the distance, and perform path planning according to the SLAM map calibrated with the obstacle boundary and the wall-following path to obtain a global movement path.

Subsequently, the controller 311 may send a command of the motion path (along the wall path) to the motion management module 318 and the cleaning management module 319 shown in fig. 2, so that the wheel assembly 323 is further driven to move by the motion management module 318, and the cleaning assembly 325 is further driven to clean by the cleaning management module 319. In one implementation, the purge management module 319 may be used to perform step 204 below, for example.

The above modules are specifically used to implement the cleaning robot control method described below, and for brevity of the description, detailed descriptions are omitted here.

Referring to fig. 4, based on the cleaning robot described above, a method for controlling the cleaning robot provided by the embodiment of the present application is described below, which is mainly described by taking an example that a sweeping device of the cleaning robot includes an edge sweep, as shown in fig. 4, and includes, but is not limited to, the following steps:

step 201, collecting images of obstacles in the operation environment of the cleaning robot.

Among the obstacles described herein are any objects encountered by the cleaning robot during its travel that may affect the movement of the cleaning robot.

Specifically, the obstacle may be an object that protrudes above the ground, such as furniture, home appliances, toys, bottled objects, animal waste, walls, wires, tea table drapes, doorsills, shoes, and the like; the obstacle may also be an object that is in close proximity to the ground, such as a water stain, a powder pile, etc. of the ground; the obstacle may be an object recessed from the ground, such as a staircase, a groove, a cliff, or the like.

In one embodiment, the cleaning robot shoots the environment through its own camera while traveling in the forward direction, and it can be understood that when there is an obstacle in front of the cleaning robot, there will be an obstacle in the shot image or video.

Step 202, identifying the type of the obstacle (which may be simply referred to as the type of the obstacle) according to the image of the obstacle.

The obstacle type represents the attribute of the obstacle, and a plurality of kinds of obstacle types can be set in the cleaning robot in advance. For example, the types of obstacles can be classified into the following:

the non-dangerous object can be close to a barrier, such as a fixed object of a wall, a table, a chair and the like.

Dangers can not be close to the similar obstacles, such as vases, recharging seats, electric wires, furniture with the same height as the cleaning robot and the like.

High risk requires the isolation of such obstacles as pet faeces, ground water stains, stairs, grooves etc.

It should be noted that the above-mentioned obstacle types are only examples, in practical applications, the dividing categories of the obstacle types may be various, and a user or a manufacturer may preset more or less obstacle types according to actual cleaning needs. For example, the obstacle types are divided into non-dangerous obstacles and dangerous obstacles (for example, dangerous inaccessible obstacles and high-dangerous obstacles may be unified into dangerous obstacles), and the like, and the present application does not limit the types.

In practical applications, the obstacle may be classified as a certain obstacle type according to the actual cleaning requirement. For example, pet feces, ground water, stairs, grooves, etc. may also be categorized as dangerous and inaccessible to obstacles, etc., which are not limited in this application.

In a specific embodiment, in the process of traveling, after the image of the obstacle is obtained through the camera, the cleaning robot can recognize the obstacle through a pre-trained deep learning model (or a deep learning algorithm) according to the image, so as to recognize the obstacle type corresponding to the obstacle. For example, the obstacle shot at present is identified as a vase through a deep learning model, and then the type of the obstacle is determined to represent that the danger is not accessible to the obstacle.

It should be noted that in other possible embodiments, the type of the obstacle may be identified by other image recognition algorithms or sensor methods.

In a specific embodiment, the cleaning robot further performs ranging using an image ranging algorithm according to the image of the obstacle, so as to obtain a distance (also referred to as a third distance) from the obstacle to the cleaning robot.

And step 203, determining the distance along the wall corresponding to the type of the obstacle.

The along-wall path represents a path trajectory of the cleaning robot after entering a mode of moving along a wall (referred to as an along-wall mode). Specifically, the wall following mode means: the cleaning robot simulates the boundary of an obstacle or a virtual boundary after expansion (the periphery of the obstacle is simultaneously expanded for a certain distance to ensure that the robot does not touch the obstacle) into an actual wall, and the cleaning robot simulates to walk for a certain distance along the wall in a mode of contacting or not contacting the obstacle. The distance between the cleaning robot and the boundary of the obstacle can be adjusted according to the type of the obstacle, and the finally formed path track is approximate to one section or the whole section of the boundary of the obstacle, namely the path along the wall.

As shown in fig. 5, the obstacle boundary is: the cleaning robot performs feature extraction (such as point cloud feature extraction) according to the image of the obstacle, so as to obtain a position feature of the outermost edge of the obstacle, and the position feature or a virtual boundary obtained by expanding the position feature can be used as a boundary of the obstacle (referred to as an obstacle boundary for short). Fig. 5 shows the cleaning robot and an obstacle with a heptagon boundary. Subsequently, the cleaning robot may map the obstacle boundaries on a SLAM map that the cleaning robot builds up with its own SLAM system.

It should be noted that, in practical applications of the cleaning robot in the embodiments of the present application, when the cleaning robot encounters an obstacle, the cleaning robot may enter the along-wall mode to travel along a wall path, and may enter the obstacle avoidance mode to travel along an obstacle avoidance path. The obstacle avoidance mode is that when the cleaning robot encounters an obstacle, the cleaning robot does not walk along the obstacle for a certain distance, but avoids the obstacle, the direction is adjusted to move and leave the obstacle, or the cleaning robot linearly backs to leave the obstacle, and a corresponding path track is an obstacle avoidance path.

In the embodiment of the present application, in order to solve the defects of the prior art in the wall-following mode, the corresponding relationship between the type of the obstacle and the distance along the wall may be preset in the cleaning robot. The distance along the wall may be used to indicate a distance between the cleaning robot and the obstacle, such as whether the cleaning robot contacts the obstacle boundary, such as how close or far the cleaning robot is to the obstacle boundary, and so on. Wherein different barrier types correspond to different spacings along the wall.

For example, in one application scenario, the types of obstacles include: non-dangerous may be near to the barrier-like, dangerous may not be near to the barrier-like, and high-dangerous may be far from the barrier-like. When the cleaning robot performs the wall-following movement along the non-dangerous and nearable obstacle, the corresponding wall-following distance of the non-dangerous and nearable obstacle is: the first distance is 1cm and the second distance is 0cm (i.e., the side sweep may directly contact the obstacle). When the cleaning robot performs the wall-following movement along the dangerous inaccessible obstacle, the corresponding wall-following distance between the dangerous inaccessible obstacle is as follows: the first distance is 5cm and the second distance is 5 cm. When cleaning robot need keep away from class barrier along high danger and carry out along wall motion, the high danger needs to keep away from the corresponding wall interval along the barrier and be: the first distance is 10cm and the second distance is 8 cm. It should be noted that the above examples are only for explanation and not for limitation. It will be appreciated that the various barrier types described above will have different paths along the wall corresponding to different distances along the wall.

In the embodiment of the application, different wall-following intervals are set for the wall-following paths corresponding to different barrier types, so that the sweeping coverage rate is as large as possible, and the safety of the barrier in a cleaning robot or the environment can be considered.

For example, when the cleaning robot encounters a solid object such as a wall, a bed foot, etc., the cleaning robot determines that the obstacles are non-dangerous and near-class obstacles, and the cleaning robot enters the along-wall mode with a smaller distance along the wall to move around the obstacles relative to the dangerous-class obstacles. As shown in fig. 6, when the cleaning robot enters the wall-following mode, the distance between the main body of the cleaning robot and the obstacle (i.e., the first distance) is small (e.g., the first distance is smaller than that in the scenario of the embodiment of fig. 7 described below), the distance between the side sweep of the cleaning robot and the obstacle (i.e., the second distance) is smaller (e.g., the second distance is smaller than that in the scenario of the embodiment of fig. 7 described below), and the second distance may even be equal to 0, i.e., the side sweep can directly contact the obstacle for sweeping, so as to maximally improve the sweeping coverage.

For another example, when the cleaning robot encounters objects such as glass bottles and refill seats, the cleaning robot determines that the obstacles are dangerous and inaccessible (because if the obstacles are close, the cleaning robot performs sweeping or the main body of the cleaning robot may collide with the refill seat to cause later charging failure or knock down the glass bottles), and compared with non-dangerous obstacles, the cleaning robot enters the wall-following path at a larger distance along the wall to move around the obstacles. As shown in fig. 7, when the cleaning robot enters the wall-following path, the first distance is larger (e.g., the first distance is larger than that in the scenario of the embodiment of fig. 6), and the second distance is also larger (e.g., the second distance is larger than that in the scenario of the embodiment of fig. 6), so as to ensure the possibility that the side-sweep and the main body of the body cannot have any contact with the obstacle. However, in the cleaning control of the cleaning robot, the values of the first distance and the second distance cannot be set too large because the values of the first distance and the second distance affect the cleaning coverage. Therefore, when the values of the first distance and the second distance are set, the safety of the obstacle is ensured, and a large cleaning coverage rate is also considered.

For another example, it can be understood that when the cleaning robot encounters objects such as animal wastes, water stains, stairs, etc., when the cleaning robot determines that the obstacles are at high risk and need to be far away from the class of obstacles, the cleaning robot adopts a mode of entering into the wall along a larger distance along the wall to move around the obstacles, i.e., the values of the first distance and the second distance are larger than those in the example of fig. 7, so as to ensure the safety of the cleaning robot and take account of a slightly larger cleaning coverage rate.

That is, in one application scenario, when the cleaning robot performs the wall-following mode, the second distance corresponding to the high-risk need-to-be-far type obstacle is greater than or equal to the second distance corresponding to the dangerous-to-be-near type obstacle, the second distance corresponding to the dangerous-to-be-near type obstacle is greater than the second distance corresponding to the non-dangerous-to-be-near type obstacle, and the second distance corresponding to the non-dangerous-to-be-near type obstacle is greater than or equal to 0.

In addition, in one application scenario, when the cleaning robot executes the wall-following mode, the first distance corresponding to the high-risk need to be far away from the barrier is greater than or equal to the first distance corresponding to the danger-inaccessible barrier; the first distance corresponding to the dangerous and inaccessible obstacle is greater than the first distance corresponding to the non-dangerous and accessible obstacle; the non-dangerous proximity to the obstacle corresponds to a first distance greater than 0.

Of course, other configurations may be performed according to actual cleaning needs, for example, when the types of obstacles in another application scenario include non-dangerous obstacles and dangerous obstacles, the distance along the wall corresponding to the dangerous obstacles is larger than the distance along the wall corresponding to the non-dangerous obstacles, where the distance along the wall corresponding to the dangerous obstacles disables the cleaning device from contacting the boundary of the obstacles, and the distance along the wall corresponding to the non-dangerous obstacles disables the cleaning device from contacting the boundary of the obstacles.

It should be noted that in a possible embodiment, the distance along the wall corresponding to the type of obstacle is not constant. The spacing along the wall may be adjusted or modified depending on a number of factors. These factors include confidence levels of obstacle boundaries, current movement speed of the cleaning robot, environmental impact on the cleaning robot, relative impact between multiple obstacles, and the like.

In one embodiment, the distance along the wall (the first distance and/or the second distance) may be inversely related to the confidence level of the obstacle boundary, and since the confidence level of the obstacle boundary is low', the likelihood of an obstacle boundary error is increased, i.e., the difficulty of achieving the path along the wall is greater, and therefore a longer distance needs to be reserved for buffering, the distance along the wall (the first distance and/or the second distance) may be greater. That is, embodiments of the present application may correct the spacing along the wall based on the confidence level of the obstacle boundary.

In one embodiment, the distance along the wall (the first distance and/or the second distance) may be in a positive relationship with the current moving speed of the cleaning robot, since the higher the current moving speed of the cleaning robot, the greater the difficulty in achieving the path along the wall, and the longer the distance to reserve as a buffer, the greater the distance along the wall (the first distance and/or the second distance). That is, the embodiment of the present application can correct the distance along the wall according to the current moving speed of the cleaning robot.

Of course, it will be appreciated that in a possible embodiment, the spacing along the wall may also be modified based on both the confidence level of the obstacle boundary and the current speed of movement of the cleaning robot.

Referring to table 1, table 1 exemplarily shows some correspondences between types of obstacles and intervals along the wall, and an example of correcting the intervals along the wall based on the confidence levels of the boundaries of the obstacles and the current moving speed.

TABLE 1

As can be seen from table 1, the barrier type is the most fundamental factor for the spacing along the wall. The distance (the first distance and/or the second distance) between the two walls can be adjusted and corrected according to the confidence level of the boundary of the obstacle, the current moving speed and other factors.

It should be noted that table 1 is only used for exemplary explanation of the relationship between the types of obstacles and the distance along the wall, and the preset conditions satisfied by the first distance and the second distance in the distance along the wall, and is not limited. In the specific application of the embodiment of the application, various obstacle types, various intervals along the wall and various corresponding relations between the obstacle types and the intervals along the wall can be preset according to the actual cleaning requirement.

It should be noted that, when the cleaning robot performs the wall following mode, the cleaning robot adjusts the direction of the original movement path to enter the wall following path, and if the housing of the cleaning robot is circular, the cleaning robot can turn around by rotating concentrically based on the wheel device. If the housing of the cleaning robot is a non-circular robot, the cleaning robot can further adjust the distance when adjusting the direction according to whether the cleaning robot will collide with an obstacle when adjusting the direction, in addition to achieving steering based on the wheel device.

It should also be noted that, in a possible embodiment, if the main body is telescopically coupled to the cleaning device; when the machine body reaches the first distance, the cleaning device can be controlled to extend and retract relative to the machine body, so that the cleaning device reaches the second distance.

And step 204, the cleaning robot moves and cleans along the wall path.

It will be appreciated that after determining the wall-following distance, the cleaning robot may plan a wall-following path for the obstacle based on the wall-following distance and the obstacle boundaries, and then control the cleaning robot to move along the wall-following path accordingly, and control the cleaning device to perform the cleaning.

It can be seen that, by implementing the embodiment of the application, the cleaning robot can distinguish different types of obstacles in the environment, and adopts different wall-following intervals to enter a wall-following mode according to different obstacle types, so that a better wall-following path can be achieved, the robot is prevented from being trapped in a threat or contacting objects (such as animal wastes) which cannot be contacted, different obstacle avoiding distances can be realized aiming at different obstacles, the far-away obstacles (such as high-risk obstacles) are ensured to be far away, the obstacles (such as non-risk obstacles) which are as close as possible are close as possible, the cleaning coverage rate can be greatly improved, meanwhile, the risks or negative influences of the obstacles and/or the cleaning robot are greatly reduced, and the cleaning safety is improved.

In addition, according to the embodiment of the application, the influence of factors such as the boundary confidence level and the moving speed of the cleaning robot can be comprehensively considered on the basis of considering the types of the obstacles, and the distance between the cleaning robots is corrected, so that the planned path along the wall is better, the path along the wall has higher accuracy and practical operability, the cleaning coverage rate is improved to the highest degree, and meanwhile, the risk or negative influence is controlled to the lowest degree.

In addition, according to the embodiment of the application, the influence of the colors of the obstacles is small, the different distances along the wall caused by the different colors of the obstacles are avoided, and some defects in the prior art are avoided.

Referring to fig. 8, based on the cleaning robot described above, a further cleaning robot control method provided in the embodiment of the present application is further described below, as shown in fig. 8, the method includes, but is not limited to, the following steps:

step 401, the cleaning robot pre-configures a path planning algorithm, a SLAM system, an image recognition algorithm, an image ranging algorithm, and the like.

The SLAM (Simultaneous Localization and Mapping, Chinese: Simultaneous Localization and Mapping) system can be used for carrying out self-Localization according to position estimation and a map in the moving process when the cleaning robot moves from an unknown position in an unknown environment, and simultaneously building an incremental map (called an SLAM map) on the basis of self-Localization, thereby realizing the autonomous Localization and navigation of the cleaning robot.

Step 402, after the cleaning robot obtains the image of the obstacle through the camera during working, the obstacle type of the obstacle is identified through an image identification algorithm according to the image of the obstacle, the obstacle boundary is obtained, and the distance (also called as a third distance) between the obstacle boundary and the cleaning robot at the moment is calculated through an image ranging algorithm. The related content can also refer to the description of step 202 in the embodiment of fig. 4, which is not described herein again.

And 403, calibrating the obstacle boundary in the SLAM map by the cleaning robot according to the distance between the obstacle boundary and the cleaning robot, so that the cleaning robot can realize self-positioning of the cleaning robot and repositioning of the obstacle at the same time according to the SLAM map. That is, subsequently, during the operation of the cleaning robot, since the obstacle boundary is calibrated in the SLAM map, the cleaning robot can also directly determine whether there is an obstacle ahead and the corresponding obstacle type according to the SLAM map.

And step 404, based on the updated SLAM map, the cleaning robot enters an obstacle avoidance processing subprogram so as to realize subsequent processing operation on the obstacle.

Step 405, the cleaning robot determines whether there is an obstacle in front. If yes, go to subsequent step 406; if the determination result is negative, step 404 is re-executed.

Specifically, in the later working process of the cleaning robot, two ways are available for judging whether an obstacle exists in front: one way is that the cleaning robot can judge whether there is an obstacle in front by shooting the image of the obstacle in real time; alternatively, when the SLAM map already has an obstacle boundary, it may also be determined whether there is an obstacle ahead of the SLAM map, and at this time, historical data may be queried to determine the type of the obstacle corresponding to the obstacle boundary.

Step 406, the cleaning robot determines whether it needs to enter the along-the-wall mode. If yes, go to subsequent step 407-step 410; if not, the following step 411 is executed.

Step 407, the cleaning robot determines the distance along the wall corresponding to the type of the obstacle, and the related contents may also refer to the description of step 203 in the embodiment of fig. 4, which is not described herein again.

Step 408, the cleaning robot plans a wall-following path for the obstacle according to the wall-following spacing.

And step 409, the cleaning robot further plans according to the SLAM map calibrated with the obstacle boundary and the determined path along the wall to obtain a global motion path.

Referring to fig. 9, in one implementation, when the cleaning robot starts to work, if it is close to an obstacle or the cleaning space is narrow, the cleaning robot may plan a simple movement path according to the SLAM map and the determined path along the wall, as shown in fig. 9, the cleaning robot finds the obstacle by shooting at a third distance, and plans the movement path. Thus, the cleaning robot can move forward in a straight line towards the obstacle, then start decelerating at a certain action starting point, pause at a position where the body is at a first distance from the obstacle boundary and at a second distance from the obstacle boundary in a side sweeping mode, adjust the direction and enter the wall-following path along the obstacle boundary.

Referring to fig. 10, in yet another implementation, if a distance from a certain obstacle is long or a swept space is large, the cleaning robot may preliminarily generate a global arcuate path from the SLAM map, and combine the arcuate path with the wall-following path to obtain a global motion path, as shown in fig. 10. Specifically, in the global movement path shown in fig. 10, when the cleaning robot moves straight toward the obstacle, if the length of the surface of the obstacle that the cleaning robot faces is less than a set length (which may be set as the length of the main body of the body), the cleaning robot may choose to wind around to the other side of the obstacle along the obstacle boundary and rotate to the backward direction consistent with the state of just entering the wall-following path to continue the zigzag sweeping. If the length of the surface of the obstacle, which is faced by the cleaning robot, is greater than the set length, the cleaning robot can select to walk along the obstacle for a distance less than or equal to the set length, then rotate to the opposite direction to the direction just before entering the wall-following path, and continue the bow-shaped cleaning. Thus, it is possible to ensure that the periphery of the obstacle can be sufficiently cleaned and covered regardless of the size of the obstacle relative to the cleaning robot.

And step 410, the cleaning robot moves and cleans according to the global motion path.

It will be appreciated that after determining the global path of movement, the cleaning robot may control the wheel assemblies to move accordingly and the sweeping assembly to sweep, depending on the specifics of the path of movement.

And 411, the cleaning robot enters an obstacle avoidance mode. The obstacle avoidance mode is that when the cleaning robot encounters an obstacle, the cleaning robot does not walk along the obstacle for a certain distance, but avoids the obstacle, and the cleaning robot adjusts the direction to move to leave the obstacle or linearly retreat to leave the obstacle.

By implementing the embodiment of the application, the cleaning robot can distinguish different types of obstacles in the environment through image detection or obstacle boundaries stored on the SLAM map, different wall-following distances are determined according to different obstacle types, so that different wall-following paths are obtained, the obstacle boundaries can be calibrated into the SLAM map, and the SLAM map and the wall-following paths are combined to perform comprehensive route planning. Like this, can enough realize different along the wall interval to different barriers to with clean the coverage and promote the highest while with risk or negative effects control to minimumly, can also have more abundant distance to formulate global movement path, consequently along the wall route can be more reasonable, more have actual maneuverability.

It should be noted that all or part of the steps in the methods of the above embodiments may be implemented by hardware instructions of a program, and the program may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an optical disc (compact disc-Read-Only Memory, CD-ROM), or other Memory, and the program may be stored in a computer-readable storage medium A tape memory, or any other medium readable by a computer that can be used to carry or store data.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to related descriptions of other embodiments for parts that are not described in detail in a certain embodiment.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a device (which may be a personal computer, a server, or a network device, a robot, a single chip, a chip, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A cleaning robot is characterized by comprising a controller and an image acquisition device; wherein:

the image acquisition device is used for acquiring images of obstacles in the operating environment of the cleaning robot;

the controller is used for identifying the type of the obstacle according to the image of the obstacle; the obstacle detection device is also used for determining the distance between the walls corresponding to the type of the obstacle, wherein different obstacle types correspond to different distances between the walls;

the controller is also used for controlling the cleaning robot to move along the wall along the boundary of the obstacle according to the distance along the wall corresponding to the type of the obstacle.

2. The cleaning robot according to claim 1,

the controller is further configured to: obtaining the reliability of the boundary of the obstacle, wherein the reliability of the boundary of the obstacle and the distance between the obstacle and the wall form an inverse correlation relationship; correcting the wall-following distance corresponding to the type of the obstacle according to the reliability of the obstacle boundary to obtain the corrected wall-following distance;

and controlling the cleaning robot to move along the wall along the barrier boundary according to the corrected distance along the wall.

3. The cleaning robot according to claim 1,

the controller is further configured to: acquiring the movement speed of the cleaning robot, wherein the movement speed of the robot is in positive correlation with the distance between the obstacles along the wall; correcting the wall-following distance of the barrier according to the movement speed of the cleaning robot to obtain the corrected wall-following distance;

4. The cleaning robot of any of claims 1-3, wherein the controller is specifically configured to identify the type of the obstacle as one of:

non-dangerous type obstacles;

a dangerous type of obstacle.

5. The cleaning robot according to claim 4,

when the type of the obstacle represents a non-dangerous obstacle, the wall-following distance is a first wall-following distance; the controller is specifically configured to control the cleaning robot to perform a wall-following motion along the obstacle boundary based on the first wall-following spacing;

when the type of the obstacle represents a dangerous obstacle, the distance between every two adjacent walls is a second distance between every two adjacent walls; the controller is specifically configured to control the cleaning robot to perform a wall-following motion along the obstacle boundary based on the second wall-following distance;

wherein the second wall-following interval is greater than the first wall-following interval.

6. The cleaning robot as claimed in claim 5, further comprising a sweeping device extending beyond an edge of the body and for sweeping a ground area beyond the edge of the body;

said first wall-following spacing causing said sweeping device to contact said barrier boundary; the second wall-wise spacing is such that the sweeping device cannot contact the obstacle boundary.

7. The cleaning robot of claim 4, wherein the dangerous type obstacle comprises at least one of:

dangerously inaccessible to the barrier-like object;

the high risk requires a distance from the obstacle.

8. The cleaning robot of claim 7, wherein the along-wall spacing is a third along-wall spacing when the type of obstacle indicates a hazard is not accessible to the obstacle-like; the controller is specifically configured to control the cleaning robot to perform a wall-following motion along the obstacle boundary based on the third wall-following distance;

when the type of the obstacle indicates that high risk needs to be kept away from the obstacle, the distance between the two walls is a fourth distance between the two walls; the controller is specifically configured to control the cleaning robot to perform a wall-following motion along the obstacle boundary based on the fourth wall-following distance;

9. The cleaning robot of any of claims 1-8, wherein the controller is further configured to determine a motion start point in a forward direction of the cleaning robot, the distance between the motion start point and the obstacle boundary being greater than the wall-following spacing;

the controller is further configured to control the cleaning robot to decelerate starting from the position of the action start point.

10. The cleaning robot according to claim 1, further comprising a cleaning device, wherein the body main body is telescopically connected to the cleaning device; the wall-following distance comprises a first distance and a second distance, the first distance is used for indicating the distance between the body and the obstacle when entering a wall-following path, and the second distance is used for indicating the distance between the cleaning device and the obstacle when entering the wall-following path;

the cleaning device is specifically configured to extend and retract relative to the machine body when the machine body reaches the first distance, so that the cleaning device reaches the second distance.

11. A cleaning robot control method, applied to a cleaning robot, the method comprising:

acquiring an image of an obstacle in an operating environment of the cleaning robot;

identifying the type of the obstacle according to the image of the obstacle;

determining the distance between the barriers along the wall corresponding to the type of the barrier, wherein different barrier types correspond to different distances between the barriers along the wall;

and controlling the cleaning robot to move along the wall along the boundary of the obstacle according to the distance along the wall corresponding to the type of the obstacle.

12. The method of claim 11, wherein after determining the distance along the wall corresponding to the type of obstacle, further comprising:

obtaining the reliability of the boundary of the obstacle, wherein the reliability of the boundary of the obstacle and the distance between the obstacle and the wall form an inverse correlation relationship; correcting the wall-following distance corresponding to the type of the obstacle according to the reliability of the obstacle boundary to obtain the corrected wall-following distance;

correspondingly, the controlling the cleaning robot to perform the wall-following movement along the boundary of the obstacle according to the wall-following distance corresponding to the type of the obstacle comprises the following steps:

13. The method of claim 11, wherein after determining the distance along the wall corresponding to the type of obstacle, further comprising:

acquiring the movement speed of the cleaning robot, wherein the movement speed of the robot is in positive correlation with the distance between the obstacles along the wall; correcting the wall-following distance of the barrier according to the movement speed of the cleaning robot to obtain the corrected wall-following distance;

14. The method according to any one of claims 11-13, wherein said identifying a type of the obstacle from the image of the obstacle comprises:

identifying a type of the obstacle as one of: non-dangerous type obstacles; a dangerous type of obstacle.

15. The method of claim 14,

16. The method of claim 15, wherein the cleaning robot further comprises a sweeping device extending beyond the edge of the fuselage body and for sweeping a ground area beyond the edge of the fuselage body;

17. The method of claim 14, wherein the dangerous type of obstacle comprises at least one of:

dangerously inaccessible to the barrier-like object;

the high risk requires a distance from the obstacle.

18. The method of claim 17, wherein the along-wall spacing is a third along-wall spacing when the type of obstacle indicates a hazard is not accessible to the obstacle-like;

19. The method according to any one of claims 11-18, wherein before controlling the cleaning robot to perform the wall-following movement along the obstacle boundary according to the wall-following distance corresponding to the type of the obstacle, further comprising:

determining an action starting point in the advancing direction of the cleaning robot, wherein the distance between the action starting point and the barrier boundary is larger than the distance between the barrier boundaries along the wall;

and controlling the cleaning robot to decelerate from the position of the action starting point.

20. The method of any one of claims 16 to 19, wherein a main body of the cleaning robot is telescopically coupled with the sweeping means of the cleaning robot; the wall-following distance comprises a first distance and a second distance, the first distance is used for indicating the distance between the body and the obstacle when entering a wall-following path, and the second distance is used for indicating the distance between the cleaning device and the obstacle when entering the wall-following path;

before controlling the cleaning robot to move along the wall along the barrier boundary according to the distance along the wall corresponding to the type of the barrier, the method further comprises the following steps:

21. A computer-readable storage medium having stored thereon program instructions which, when executed, implement the method of any one of claims 11-20.