Robot obstacle avoidance control method and mobile robot

Abstract

The invention provides a robot obstacle avoidance control method and a mobile robot, and the mobile robot divides an area scanned by a line laser module into a plurality of sub-areas, and more accurately marks the distribution condition of obstacles, so that a reasonable obstacle avoidance direction can be more intelligently selected, the obstacle avoidance direction problem is solved, and the obstacle avoidance efficiency is improved. The path planned by the robot is smoother, and the obstacle avoidance capability of the robot is greatly improved. And meanwhile, the mobile robot can be switched in one step when encountering an obstacle, so that the smoothness of the robot along the edge is greatly improved, and the working efficiency and the cruising ability of the robot are also improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent robots, and in particular to a robot obstacle avoidance control method and a mobile robot. Background Art

[0002] Nowadays, more and more families are choosing to use sweeping robots to clean the floor. However, during use, many users found that the obstacle avoidance ability and cleaning efficiency of sweeping robots vary. For example, some sweeping robots are often blocked by obstacles on the ground, or they bump into tables, chairs and benches without thinking because of route planning problems, affecting the sweeping efficiency. One of the reasons for this problem is that the sweeping robot does not mark obstacles finely enough. Obstacles marked by general collision sensors or visual sensors will be clumped together on the map, which is not conducive to the sweeping robot's planning of the cleaning path, greatly reducing the sweeping robot's obstacle avoidance ability. Another reason that affects the sweeping efficiency is that the sweeping robot is not smooth along the edge. Some sweeping robots use the alternating form of long and short along the edge, which makes it impossible for the sweeping robot to switch along the edge in one step when encountering obstacles. It is necessary to repeatedly turn and adjust the position of the edge sensor. This way of following the edge is not only time-consuming and energy-consuming, but also affects the user experience. Summary of the invention

[0003] The present application provides a robot obstacle avoidance control method and a mobile robot, and the specific technical solutions are as follows:

[0004] A robot obstacle avoidance control method, the operation method comprising: step S1, during the scanning process of a line laser module, the robot divides the area scanned by the line laser module into a plurality of sub-areas, and marks obstacles on the sub-areas respectively; step S2, the robot determines the obstacle distribution on the sub-areas according to the obstacle marks, and then plans the robot's operation path according to the positional relationship between the obstacles and the non-operated areas; step S3, based on the robot's operation path, when there is an obstacle in front of the robot, the point cloud data of the line laser module is obtained and processed to obtain point cloud data that meets preset conditions; step S4, the angle of the obstacle relative to the robot is calculated to obtain the rotation angle required for the robot to avoid the obstacle; step S5, when the obstacle avoidance condition is triggered, the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle.

[0005] Furthermore, in step S1, the area scanned by the line laser module is located directly in front of the robot, the length of the area is equal to the length of the line laser emitted by the line laser module, and the area is equally divided into a number of sub-areas.

[0006] Furthermore, in step S1, the method for marking obstacles on the sub-areas includes: step S11, the robot obtains point cloud data of the line laser module and equally divides it into several data intervals, each corresponding to a number of sub-areas; step S12, respectively calculates the height averages of the point cloud data in the several data intervals, and then compares the height average with the preset height; if the height average is greater than or equal to the preset height, an obstacle is marked on the sub-area corresponding to the height average.

[0007] Furthermore, in the step S2, the method for planning the robot's working path according to the positional relationship between obstacles and non-operated areas includes: step S21, during the operation process, the robot determines whether there are obstacles in several sub-areas according to obstacle marks, if there are obstacles in all sub-areas, the robot turns around, if there are obstacles in some sub-areas, the robot enters step S22; step S22, the robot determines the positional relationship between the obstacle and the non-operated area, if at least one sub-area with an obstacle is connected to the non-operated area, the robot turns around, if at least one sub-area without obstacles is connected to the non-operated area, the robot bypasses the obstacle through the sub-area without obstacles.

[0008] Furthermore, in step S22, when at least one sub-area where an obstacle exists is connected to the non-operating area, the robot first executes obstacle avoidance and makes a judgment. If the robot does not move to the next operating path during the obstacle avoidance process, the robot continues to execute obstacle avoidance until the obstacle avoidance is successful. If the robot moves to the next operating path during the obstacle avoidance process, the obstacle avoidance is terminated and the robot turns around.

[0009] Furthermore, in the step S3, the point cloud data of the line laser module is obtained and processed to obtain the point cloud data that meets the preset conditions. The method includes: step S31, after obtaining the point cloud data of the line laser module, retaining the point cloud data whose height exceeds the preset height; step S32, every preset angle, from one end to the other end of the point cloud data, take a point cloud data at each angle. If there is only one point cloud data at an angle, then the point cloud data is the point cloud data that meets the preset conditions. If there are multiple point cloud data at an angle, go to step S13; step S33, compare the distances between the multiple point cloud data and the robot, take the minimum distance value, and at the same time perform mean filtering on the heights of the multiple point cloud data to obtain the average height value, and take the point cloud data with the minimum distance value and the average height value as the only point cloud data at the angle.

[0010] Furthermore, in the step S3, the method of acquiring and processing the point cloud data of the line laser module to obtain point cloud data that meets the preset conditions also includes: step S34, each time after acquiring the line laser data, executing steps S11 to S13 to obtain the point cloud data that meets the preset conditions in the frame of line laser data; step S35, comparing the point cloud data that meets the preset conditions in the frame of line laser data with the point cloud data that meets the preset conditions in the previous frame of line laser data, and at each angle, taking the point cloud data with the largest height and closest to the robot as the new point cloud data that meets the preset conditions.

[0011] Furthermore, in step S4, the method for calculating the angle of the obstacle relative to the robot includes step S41, calculating the mean of all point cloud data that meet the preset conditions, denoted as Step S42, calculating the regression coefficient b through the linear regression equation, Among them, the regression coefficient b is the angle of the obstacle relative to the robot.

[0012] Furthermore, in step S5, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: step S51, calculating the distance a between the robot and the obstacle, Step S52, determine whether the distance a between the robot and the obstacle is less than the preset distance. If so, trigger the obstacle avoidance condition; Step S53, according to the preset direction, the robot rotates according to the rotation angle b to avoid the obstacle along the edge of the obstacle.

[0013] A mobile robot, which is used to implement the robot obstacle avoidance control method, and includes a line laser module and an edge sensor, wherein the line laser module is arranged at the front end of the mobile robot, and the line laser emitted by the line laser module is a horizontal straight line inclined downward, which is used to obtain point cloud data to calculate the angle of the obstacle relative to the robot, so as to obtain the rotation angle required for the mobile robot to avoid the obstacle, and the mobile robot divides the area scanned by the line laser module into several sub-areas, and marks the obstacles on the sub-areas respectively; the edge sensor is arranged on the side of the mobile robot, and when the obstacle avoidance condition is triggered, the mobile robot rotates according to the rotation angle so that the edge sensor is just aligned with the obstacle to avoid the obstacle along the edge of the obstacle.

[0014] The robot obstacle avoidance control method described in the present application divides the area scanned by the line laser module into several sub-areas, more accurately marks the distribution of obstacles, and then plans the robot's operating path based on the positional relationship between the obstacle distribution in the sub-area and the non-operating area. Compared with the collision sensor or infrared sensor, it can more intelligently select a reasonable obstacle avoidance direction, solve the problem of obstacle avoidance direction, make the robot's planned path smoother, and greatly improve the robot's obstacle avoidance ability. At the same time, the point cloud data obtained by the line laser module determines the positional relationship between the robot and the obstacle, and calculates the angle that the robot needs to rotate when avoiding obstacles along the edge, so that the robot can turn to a direction parallel to the obstacle, thereby ensuring that the side edge sensor can accurately align with the obstacle. The edge method enables the robot to switch to the edge in one step when encountering an obstacle, greatly improving the smoothness of the robot when following the edge, and also improving the robot's work efficiency and endurance. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flowchart of a robot obstacle avoidance control method according to an embodiment of the present application. DETAILED DESCRIPTION

[0016] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0017] It should be understood that when used in this application, the term "comprising" indicates the presence of the described features, integral bodies, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integral bodies, steps, operations, elements, components and / or their collections. It should also be understood that the term "and / or" used in this application refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0018] As used in this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0019] In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. The reference to "one embodiment" or "some embodiments" described in the specification of the present application means that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in the differences in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0020] Nowadays, more and more families are choosing to use sweeping robots to clean the floor. However, during use, many users found that the obstacle avoidance ability and cleaning efficiency of sweeping robots vary. For example, some sweeping robots are often blocked by obstacles on the ground, or they bump into tables, chairs and benches without thinking because of route planning problems, affecting the sweeping efficiency. One of the reasons for this problem is that the sweeping robot does not mark obstacles finely enough. Obstacles marked by general collision sensors or visual sensors will be clumped together on the map, which is not conducive to the sweeping robot's planning of the cleaning path, greatly reducing the sweeping robot's obstacle avoidance ability. Another reason that affects the sweeping efficiency is that the sweeping robot is not smooth along the edge. Some sweeping robots use the alternating form of long and short along the edge, which makes it impossible for the sweeping robot to switch along the edge in one step when encountering obstacles. It is necessary to repeatedly turn and adjust the position of the edge sensor. This way of following the edge is not only time-consuming and energy-consuming, but also affects the user experience.

[0021] In order to solve the above technical problems, the present application provides a robot obstacle avoidance control method, such as Figure 1 As shown, the operation method includes:

[0022] Step S1, during the scanning process of the line laser module, the robot divides the area scanned by the line laser module into several sub-areas, and marks obstacles on the sub-areas respectively;

[0023] Step S2, the robot determines the distribution of obstacles in the sub-area according to the obstacle marks, and then plans the robot's operating path according to the positional relationship between the obstacles and the non-operated area;

[0024] Step S3, based on the robot's working path, when there is an obstacle in front of the robot, the point cloud data of the line laser module is acquired and processed to obtain point cloud data that meets the preset conditions;

[0025] Step S4, calculating the angle of the obstacle relative to the robot, and obtaining the rotation angle required for the robot to avoid the obstacle;

[0026] Step S5, when the obstacle avoidance condition is triggered, the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle, wherein after the robot rotates according to the rotation angle, the forward direction of the robot is parallel to the obstacle and moves along the edge in a straight line.

[0027] It should be noted that the line laser module emits an infrared laser through a laser transmitter and scans the target object. The receiver then receives the reflected light and calculates the three-dimensional coordinate information of the target object based on the calibrated relative position between the receiver and the laser transmitter. Information such as height, distance and angle can be obtained, thereby completing the precise positioning of the target object.

[0028] As one implementation, in step S1, the area scanned by the line laser module is located directly in front of the robot, the length of the area is equal to the length of the line laser emitted by the line laser module, and the area is equally divided into several sub-areas. The method described in this embodiment can more accurately indicate the distribution of obstacles.

[0029] As one of the implementation modes, in step S1, the method of marking obstacles on the sub-areas includes: step S11, the robot obtains the point cloud data of the line laser module and equally divides it into several data intervals, which correspond to several sub-areas respectively; step S12, respectively calculates the height average of the point cloud data in several data intervals, and then compares the height average with the preset height. If the height average is greater than or equal to the preset height, an obstacle mark is made on the sub-area corresponding to the height average. Wherein, when a sub-area has the obstacle mark, it indicates that there is an obstacle in the sub-area. The obstacle mark can be represented by a grayscale value. Preferably, the preset height is 1.8 cm, and the robot can directly cross obstacles with an average height lower than 1.8 cm without marking the obstacles, or make other marks different from the obstacle mark type, such as obstacle crossing marks.

[0030] As one of the implementation modes, in step S2, the method for planning the robot's operation path according to the positional relationship between obstacles and non-operating areas includes: step S21, during the operation, the robot determines whether there are obstacles in several sub-areas according to the obstacle marks, if there are obstacles in all sub-areas, the robot turns around, if there are obstacles in some sub-areas, then enters step S22; step S22, the robot determines the positional relationship between the obstacle and the non-operating area, if at least one sub-area with obstacles is connected to the non-operating area, the robot turns around, if at least one sub-area without obstacles is connected to the non-operating area, the robot bypasses the obstacle through the sub-area without obstacles. The method described in this embodiment enables the robot to more intelligently select the obstacle avoidance method or obstacle bypassing direction based on the precise obstacle distribution, thereby improving the rationality and fluency of path planning.

[0031] As one of the implementation modes, in the step S22, when at least one sub-area where obstacles exist is connected to the non-operating area, the robot first executes obstacle avoidance and makes a judgment. If the robot does not move to the next operating path during the obstacle avoidance process, the robot continues to execute obstacle avoidance until the obstacle avoidance is successful. If the robot moves to the next operating path during the obstacle avoidance process, the obstacle avoidance is terminated and the robot turns around. The method described in this embodiment can ensure the rationality of the robot's operation, avoid the robot from moving to a farther area due to obstacle avoidance, and also avoid the occurrence of missed areas. It should be noted that the robot of the present application plans the operating path in a bow-shaped manner, and the above-mentioned operating path refers to the long side of the bow-shaped path. In the present application, when the robot encounters an obstacle on the short side, conventional methods are used to avoid obstacles and return to the long side.

[0032] As one of the implementation methods, the robot divides the area scanned by the line laser module into four sub-areas, including the first sub-area, the second sub-area, the third sub-area and the fourth sub-area. In one embodiment, the length of the line laser emitted by the line laser module is 40 cm, which is equivalent to the diameter of the robot, and the length of each sub-area is 10 cm. The total length of the sub-areas just corresponds to the diameter of the robot, which is convenient for the robot to grasp the location of obstacles and reasonably plan the operation path.

[0033] Based on the above embodiment, when there are obstacles in the first sub-area, the second sub-area, the third sub-area and the fourth sub-area, the robot directly turns around to operate. When there is no obstacle in the fourth sub-area (assuming that the fourth sub-area is connected to the non-operated area), and there is an obstacle in at least one of the other three sub-areas, the robot uses the fourth sub-area to bypass the obstacle. During the obstacle bypassing process, the line laser module will continue to scan, or obtain information through the historical map on whether the non-operated area connected to the fourth sub-area is passable. If the length of the adjacent sub-area without obstacles is less than the diameter of the robot, the robot will change the obstacle bypassing operation to a U-turn operation. When there is an obstacle in at least the fourth sub-area, the robot first tries to bypass the obstacle, and turns around if the obstacle bypassing fails.

[0034] The robot obstacle avoidance control method divides the area scanned by the line laser module into several sub-areas, more accurately marks the distribution of obstacles, and then plans the robot's operating path according to the positional relationship between the obstacle distribution in the sub-areas and the non-operating area. Compared with collision sensors or infrared sensors, it can more intelligently select a reasonable obstacle avoidance direction, solve the problem of obstacle avoidance direction, make the robot's planned path smoother, and greatly improve the robot's obstacle avoidance ability.

[0035] As one of the implementation modes, in step S3, the point cloud data of the line laser module is obtained and processed to obtain the point cloud data that meets the preset conditions, which includes: step S31, after obtaining the point cloud data of the line laser module, retain the point cloud data whose height exceeds the preset height; step S32, every preset angle, from one end to the other end of the point cloud data, take a point cloud data at each angle, if there is only one point cloud data at an angle, then the point cloud data is the point cloud data that meets the preset conditions, if there are multiple point cloud data at an angle, then enter step S13; step S33, compare the distance between multiple point cloud data and the robot, take the minimum distance value, and perform mean filtering on the height of multiple point cloud data to obtain the average height value, and take the point cloud data with the minimum distance value and the average height value as the only point cloud data at the angle. Among them, it is known that the line laser module hits a straight line on the obstacle, and the straight line has two endpoints, and the point cloud data is selected from one end to the other end of the straight line. Preferably, a point cloud data is selected every 1 degree on the straight line to facilitate subsequent calculations.

[0036] As one of the implementation modes, in step S3, the method of obtaining point cloud data of the line laser module and processing it to obtain point cloud data that meets the preset conditions also includes: step S34, each time after obtaining line laser data, executing steps S11 to S13 to obtain point cloud data that meets the preset conditions in the frame of line laser data; step S35, comparing the point cloud data that meets the preset conditions in the frame of line laser data with the point cloud data that meets the preset conditions in the previous frame of line laser data, and at each angle, taking the point cloud data with the highest height and closest to the robot as the new point cloud data that meets the preset conditions. The method described in this embodiment can obtain point cloud data that can more accurately represent obstacles.

[0037] As one implementation method, in step S4, the method for calculating the angle of the obstacle relative to the robot includes step S41, calculating the mean of all point cloud data that meet the preset conditions, denoted as Step S42, calculating the regression coefficient b through the linear regression equation, Among them, the regression coefficient b is the angle of the obstacle relative to the robot.

[0038] Generally, when a robot encounters an obstacle, it will randomly rotate an angle, and then follow the edge in an alternating manner of near and far. Since the rotation angle is not calculated, the robot needs to constantly adjust its position so that the side edge sensor can be aimed at the obstacle. As a result, the robot's edge-following process will appear clumsy, and time and power will be wasted in repeated adjustments, affecting work efficiency. Therefore, calculating the angle b that the robot needs to rotate when encountering an obstacle can allow the robot to switch to edge-following in one step, improve the smoothness of the edge-following process, and thus improve the robot's work efficiency and endurance.

[0039] As one embodiment, in step S5, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: step S51, calculating the distance a between the robot and the obstacle, Step S52, determine whether the distance a between the robot and the obstacle is less than the preset distance, if so, trigger the obstacle avoidance condition; step S53, according to the preset direction, the robot rotates according to the rotation angle b to avoid the obstacle along the edge of the obstacle. Among them, when the distance between the robot and the obstacle is less than the preset distance, that is, the robot is close enough to the obstacle, the obstacle avoidance is performed, which can increase the working area of ​​the robot and improve the work quality. It should be noted that in this application, the obstacle is regarded as a straight line, and the straight line equation representing the obstacle can be obtained by fitting the point cloud data through the straight line regression equation.

[0040] The robot obstacle avoidance control method determines the positional relationship between the robot and the obstacle through the point cloud data obtained by the line laser module, and calculates the angle that the robot needs to rotate when avoiding obstacles along the edge, so that the robot can turn to a direction parallel to the obstacle, thereby ensuring that the side edge sensor can accurately align with the obstacle. The edge method enables the robot to switch to edge in one step when encountering an obstacle, greatly improving the smoothness of the robot when following the edge, and also improving the robot's work efficiency and endurance.

[0041] The present application also provides a mobile robot, the mobile robot is used to implement the robot obstacle avoidance control method, the mobile robot includes a line laser module and an edge sensor, wherein the line laser module is arranged at the front end of the mobile robot, and the line laser emitted by the line laser module is a horizontal straight line inclined downward, which is used to obtain point cloud data to calculate the angle of the obstacle relative to the robot, so as to obtain the rotation angle required for the mobile robot to avoid the obstacle, and the mobile robot divides the area scanned by the line laser module into several sub-areas, and marks the obstacles on the sub-areas respectively; the edge sensor is arranged on the side of the mobile robot, when the obstacle avoidance condition is triggered, the mobile robot rotates according to the rotation angle, so that the edge sensor is just aligned with the obstacle to avoid the obstacle along the edge of the obstacle, wherein after the robot rotates according to the rotation angle, the robot's forward direction is parallel to the obstacle, and the robot moves along the edge in a straight line. The mobile robot described in the present application divides the area scanned by the line laser module into several sub-areas, more accurately marks the distribution of obstacles, so that a reasonable obstacle avoidance direction can be selected more intelligently, the problem of obstacle avoidance direction is solved, the path planned by the robot is smoother, and the robot's obstacle avoidance ability is greatly improved. At the same time, when the mobile robot encounters an obstacle and switches to following the edge, it can be in place in one step, which greatly improves the smoothness of the robot when following the edge, and also improves the robot's work efficiency and endurance.

[0042] As one implementation, the number of the line laser module is 1, the number of the edge sensors is 2, and the edge sensors are respectively arranged on the left and right sides of the mobile robot. A single line laser module can be used to obtain the rotation angle required for the robot to avoid obstacles, which has a simple structure, low cost, and high practical value.

[0043] As one implementation method, the line laser module is ALF02-S, which includes a straight line laser and a camera, has high precision and good effect. The camera is a camera specially used to receive infrared laser.

[0044] The present application also provides a chip, the chip stores a computer program code, and the computer program code implements the robot obstacle avoidance control method when executed. The chip is set in the above-mentioned mobile robot, so that the path planned by the mobile robot is smoother, greatly improving the obstacle avoidance ability of the mobile robot, and when encountering an obstacle, switching along the edge can be done in one step, greatly improving the smoothness of the mobile robot when following the edge, and also improving the working efficiency and endurance of the mobile robot.

[0045] It will be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the references to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory ROM, programmable memory PROM, electrically programmable memory DPROM, electrically erasable programmable memory DDPROM or flash memory. Volatile memory may include random access memory RAM or external cache memory.

[0046] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0047] The above embodiments only express several embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A robot obstacle avoidance control method, characterized in that: The operation method comprises: Step S1, during the scanning process of the line laser module, the robot divides the area scanned by the line laser module into several sub-areas, and marks obstacles on the sub-areas respectively; Step S2, the robot determines the distribution of obstacles in the sub-area according to the obstacle marks, and then plans the robot's operating path according to the positional relationship between the obstacles and the non-operated area; Step S3, based on the robot's working path, when there is an obstacle in front of the robot, the point cloud data of the line laser module is acquired and processed to obtain point cloud data that meets the preset conditions; Step S4, calculating the angle of the obstacle relative to the robot, and obtaining the rotation angle required for the robot to avoid the obstacle; Step S5: When the obstacle avoidance condition is triggered, the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle.

2. A robot obstacle avoidance control method according to claim 1, characterized in that: In the step S1, the area scanned by the line laser module is located directly in front of the robot. The length of the area is equal to the length of the line laser emitted by the line laser module, and the area is equally divided into several sub-areas.

3. A robot obstacle avoidance control method according to claim 2, characterized in that: In step S1, the method of marking obstacles on the sub-areas includes: Step S11, the robot obtains point cloud data of the line laser module and equally divides it into a number of data intervals, each corresponding to a number of sub-areas; Step S12, respectively calculate the average height of the point cloud data in several data intervals, and then compare the average height with the preset height. If the average height is greater than or equal to the preset height, mark the obstacle on the sub-area corresponding to the average height.

4. A robot obstacle avoidance control method according to claim 3, characterized in that: In step S2, the method for planning the robot's operating path according to the positional relationship between the obstacle and the non-operating area includes: Step S21: During the operation, the robot determines whether there are obstacles in several sub-areas according to the obstacle marks. If there are obstacles in all sub-areas, the robot turns around. If there are obstacles in some sub-areas, the robot proceeds to step S22. In step S22, the robot determines the positional relationship between the obstacle and the non-operated area. If at least one sub-area with an obstacle is connected to the non-operated area, the robot turns around. If at least one sub-area without an obstacle is connected to the non-operated area, the robot bypasses the obstacle through the sub-area without an obstacle.

5. A robot obstacle avoidance control method according to claim 4, characterized in that: In step S22, when at least one sub-area with obstacles is connected to the non-operating area, the robot first performs obstacle avoidance and makes a judgment. If the robot does not move to the next operating path during the obstacle avoidance process, the robot continues to perform obstacle avoidance until the obstacle avoidance is successful. If the robot moves to the next operating path during the obstacle avoidance process, the obstacle avoidance is terminated and the robot turns around.

6. A robot obstacle avoidance control method according to claim 5, characterized in that: In step S3, the method of acquiring and processing the point cloud data of the line laser module to obtain the point cloud data that meets the preset conditions includes: Step S31, after acquiring the point cloud data of the line laser module, retain the point cloud data with a height exceeding a preset height; Step S32, every preset angle, from one end to the other end of the point cloud data, take a point cloud data at each angle, if there is only one point cloud data at an angle, then the point cloud data is the point cloud data that meets the preset conditions, if there are multiple point cloud data at one angle, then go to step S13; Step S33, compare the distances between multiple point cloud data and the robot, take the minimum distance value, and perform mean filtering on the heights of multiple point cloud data to obtain the average height value. The point cloud data with the minimum distance value and the average height value is used as the only point cloud data at this angle.

7. A robot obstacle avoidance control method according to claim 6, characterized in that: In step S3, the method of acquiring and processing the point cloud data of the line laser module to obtain the point cloud data that meets the preset conditions also includes: Step S34, after each acquisition of line laser data, executing steps S11 to S13 to obtain point cloud data that meets preset conditions in the frame of line laser data; Step S35, compare the point cloud data in the frame line laser data that meets the preset conditions with the point cloud data in the previous frame line laser data that meets the preset conditions, and at each angle, use the point cloud data with the largest height and closest to the robot as the new point cloud data that meets the preset conditions.

8. A robot obstacle avoidance control method according to claim 6 or 7, characterized in that: In step S4, the method for calculating the angle of the obstacle relative to the robot includes: Step S41, calculate the mean of all point cloud data that meet the preset conditions, denoted as Step S42, calculating the regression coefficient b through the linear regression equation, Among them, the regression coefficient b is the angle of the obstacle relative to the robot.

9. A robot obstacle avoidance control method according to claim 8, characterized in that: In step S5, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: Step S51, calculate the distance a between the robot and the obstacle, Step S52, determining whether the distance a between the robot and the obstacle is less than a preset distance, and if so, triggering an obstacle avoidance condition; Step S53: According to a preset direction, the robot rotates according to a rotation angle b to avoid the obstacle along the edge of the obstacle.

10. A mobile robot, characterized in that: The mobile robot is used to implement the robot obstacle avoidance control method according to any one of claims 1 to 9, and the mobile robot includes a line laser module and an edge sensor, wherein: The line laser module is arranged at the front end of the mobile robot, and the line laser emitted by the line laser module is a horizontal straight line obliquely downward, which is used to obtain point cloud data to calculate the angle of the obstacle relative to the robot, so as to obtain the rotation angle required for the mobile robot to avoid the obstacle, and the mobile robot divides the area scanned by the line laser module into several sub-areas, and marks the obstacles on the sub-areas respectively; The edge sensor is arranged on the side of the mobile robot. When the obstacle avoidance condition is triggered, the mobile robot rotates according to the rotation angle so that the edge sensor is just aligned with the obstacle to avoid the obstacle along the edge of the obstacle.

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