Robot edgewise method, mobile robot and chip

Abstract

The invention provides a robot edgewise method, a mobile robot and a chip, the position relation between the robot and an obstacle is judged through point cloud data obtained by a line laser module, and the required rotation angle of the robot during obstacle avoidance along the edge is calculated, so that the robot can rotate to the direction parallel to the obstacle, and the obstacle avoidance efficiency is improved. Therefore, it is ensured that the side edge sensor can be accurately aligned with the obstacle. According to the edging method, the robot can be switched in one step when encountering the obstacle, the edging smoothness of the robot 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 edge-adjacent method, a mobile robot and a chip. 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 problems with route planning, affecting the sweeping efficiency. One reason that affects the sweeping efficiency is that the sweeping robot does not move smoothly along the edge. Some sweeping robots use a long and short alternating form of moving along the edge, which makes it impossible for the sweeping robot to switch along the edge in one step when encountering an obstacle. It needs to repeatedly turn and adjust the position of the edge sensor. This way of moving along 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 edge-adjacent method, a mobile robot and a chip. The specific technical solutions are as follows:

[0004] A robot edge-following method, the edge-following method comprising: step S1, acquiring and processing line laser data to obtain point cloud data that meets preset conditions, wherein the point cloud data is used to represent an obstacle; step S2, calculating the angle of the obstacle relative to the robot to obtain the rotation angle required for the robot to avoid the obstacle; step S3, 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 robot's forward direction is parallel to the obstacle, and the robot follows the edge in a straight line.

[0005] Furthermore, in the step S1, the method of acquiring and processing line laser data to obtain point cloud data that meets preset conditions includes: step S11, after acquiring the line laser data, retaining the point cloud data whose height exceeds the preset height; step S12, taking a point cloud data at each angle from one end to the other end of the line laser data at every preset 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 proceed to step S13; step S13, compare the distances between the multiple point cloud data and the robot, take the minimum distance value therebetween, and at the same time perform mean filtering on the heights of the multiple point cloud data to obtain an average height value, and use the point cloud data with the minimum distance value and the average height value as the only point cloud data at the angle.

[0006] Furthermore, in the step S1, the method of acquiring and processing line laser data to obtain point cloud data that meets preset conditions also includes: step S14, executing steps S11 to S13 each time after acquiring line laser data, to obtain point cloud data that meets the preset conditions in the frame of line laser data; step S15, 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.

[0007] Furthermore, in step S2, the method for calculating the angle of the obstacle relative to the robot includes: step S21, calculating the mean of all point cloud data that meet the preset conditions, denoted as Step S22, 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.

[0008] Furthermore, in step S3, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: step S31, calculating the distance a between the robot and the obstacle, Step S32, determine whether the distance a between the robot and the obstacle is less than the preset distance. If so, the obstacle avoidance condition is triggered; Step S33, according to the preset direction, the robot rotates according to the rotation angle b to avoid the obstacle along the edge of the obstacle.

[0009] A mobile robot is used to implement the robot edge-following method, 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 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; 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, wherein after the robot rotates according to the rotation angle, the robot's forward direction is parallel to the obstacle, and it moves along the edge in a straight line.

[0010] Furthermore, 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.

[0011] Furthermore, the model of the line laser module is ALF02-S, which includes a straight line laser and a camera.

[0012] Furthermore, the edge sensor is an infrared sensor.

[0013] A chip stores computer program code, and the computer program code implements the robot edge-following method when executed.

[0014] The robot edge-following method described in this application 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-following sensor can accurately align with the obstacle. The edge-following method allows the robot to switch to edge-following 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 schematic flow chart of a robot edge following 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 problems with route planning, affecting the sweeping efficiency. One reason that affects the sweeping efficiency is that the sweeping robot does not move smoothly along the edge. Some sweeping robots use a long and short alternating form of moving along the edge, which makes it impossible for the sweeping robot to switch along the edge in one step when encountering an obstacle. It needs to repeatedly turn and adjust the position of the edge sensor. This way of moving along 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 edge-following method, which 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-following method enables the robot to switch to edge-following 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.

[0022] like Figure 1 As shown, the edge method includes:

[0023] Step S1, acquiring and processing line laser data to obtain point cloud data that meets preset conditions, wherein the point cloud data is used to represent obstacles;

[0024] Step S2, calculating the angle of the obstacle relative to the robot, and obtaining the rotation angle required for the robot to avoid the obstacle;

[0025] Step S3, 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.

[0026] 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.

[0027] As one of the implementation modes, in the step S1, the method of obtaining line laser data and processing it to obtain point cloud data that meets the preset conditions includes: step S11, after obtaining the line laser data, retaining the point cloud data whose height exceeds the preset height; step S12, taking a point cloud data at each angle from one end to the other end of the line laser data at every preset 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 S13, 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.

[0028] As one of the implementation modes, in step S1, the method of acquiring and processing line laser data to obtain point cloud data that meets the preset conditions also includes: step S14, each time after acquiring 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 S15, 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.

[0029] As one implementation method, in step S2, the method for calculating the angle of the obstacle relative to the robot includes: step S21, calculating the mean of all point cloud data that meet the preset conditions, denoted as Step S22, 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.

[0030] 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.

[0031] As one embodiment, in step S3, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: step S31, calculating the distance a between the robot and the obstacle, Step S32, determine whether the distance a between the robot and the obstacle is less than the preset distance. If so, the obstacle avoidance condition is triggered; Step S33, the robot rotates according to the preset direction 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 with a straight line regression equation.

[0032] The present application also provides a mobile robot, which is used to implement the robot edge-following method, 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 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; 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, wherein after the robot rotates according to the rotation angle, the robot's forward direction is parallel to the obstacle, and the edge is performed in a straight line. The mobile robot described in the present application 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-following method enables the robot to switch to edge-following in one step when encountering an obstacle, which greatly improves the smoothness of the robot when following the edge, and also improves the robot's work efficiency and endurance.

[0033] 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.

[0034] 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.

[0035] As one implementation manner, the edge sensor is an infrared sensor. The edge sensor may also be a line laser module, which is not limited here.

[0036] The present application also provides a chip, wherein the chip stores a computer program code, and when the computer program code is executed, the robot edge-following method is implemented. The chip is arranged in the mobile robot, so that when the mobile robot encounters an obstacle and switches to edge-following, it can be done in one step, which greatly improves the smoothness of the mobile robot when edge-following, and also improves the working efficiency and endurance of the mobile robot.

[0037] 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.

[0038] 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.

[0039] 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 edge following method, characterized in that: The edge method comprises: Step S1, acquiring and processing line laser data to obtain point cloud data that meets preset conditions, wherein the point cloud data is used to represent obstacles; Step S2, calculating the angle of the obstacle relative to the robot, and obtaining the rotation angle required for the robot to avoid the obstacle; Step S3, 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.

2. A robot edge following method according to claim 1, characterized in that: In step S1, the method of acquiring and processing line laser data to obtain point cloud data that meets preset conditions includes: Step S11, after acquiring the line laser data, retaining the point cloud data whose height exceeds the preset height; Step S12, every preset angle, from one end to the other end of the line laser 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, go to step S13; Step S13, 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.

3. A robot edge following method according to claim 2, characterized in that: In step S1, the method of acquiring and processing line laser data to obtain point cloud data that meets preset conditions also includes: Step S14, 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 S15, 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.

4. A robot edge following method according to claim 2 or 3, characterized in that: In step S2, the method for calculating the angle of the obstacle relative to the robot includes: Step S21, calculate the mean of all point cloud data that meet the preset conditions, denoted as Step S22, 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.

5. A robot edge following method according to claim 4, characterized in that: In step S3, the method in which the robot rotates according to the rotation angle to avoid the obstacle along the edge of the obstacle includes: Step S31, calculate the distance a between the robot and the obstacle, Step S32, 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 S33: According to a preset direction, the robot rotates according to a rotation angle b to avoid the obstacle along the edge of the obstacle.

6. A mobile robot, characterized in that: The mobile robot is used to implement the robot edge-following method according to any one of claims 1 to 5, and the mobile robot comprises a line laser module and an edge-following sensor, wherein: The line laser module is arranged at the front end of the mobile robot, and the line laser emitted by the 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, thereby obtaining the rotation angle required for the mobile robot to avoid the obstacle; 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 exactly aligned with the obstacle to avoid the obstacle along the edge of the obstacle. After the robot rotates according to the rotation angle, the robot's forward direction is parallel to the obstacle and moves along the edge in a straight line.

7. A mobile robot according to claim 6, characterized in that: 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.

8. A mobile robot according to claim 7, characterized in that: The model of the line laser module is ALF02-S, which includes a straight line laser and a camera.

9. The mobile robot according to claim 7, characterized in that: The edge sensor is an infrared sensor.

10. A chip storing computer program code, characterized in that: When the computer program code is executed, the robot edge following method according to any one of claims 1 to 5 is implemented.

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