WO2021004328A1

WO2021004328A1 - Mobile robot and localization method therefor, and computer-readable storage medium

Info

Publication number: WO2021004328A1
Application number: PCT/CN2020/099229
Authority: WO
Inventors: 杨勇; 吴泽晓; 胡志远
Original assignee: 深圳市杉川机器人有限公司
Priority date: 2019-07-11
Filing date: 2020-06-30
Publication date: 2021-01-14
Also published as: CN110340877A; CN110340877B

Abstract

A localization method for a mobile robot, comprising: determining a first area where the mobile robot is located, and scattering particles in the first area for Monte Carlo localization; and after the localization fails, determining a second area where the mobile robot is located and scattering particles for Monte Carlo localization, wherein the area of the first area is less than that of the second area, and the number of particles scattered by the mobile robot in the first area is less than the number of particles scattered by the mobile robot in the second area. The localization method improves the localization efficiency of the mobile robot. Also disclosed are the mobile robot and a computer-readable storage medium.

Description

Mobile robot and its positioning method and computer readable storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on July 11, 2019, the application number is 201910623793.5, and the invention title is "mobile robot and its positioning method and computer-readable storage medium", the entire content of which is by reference Incorporate in the application.

Technical field

This application relates to the technical field of mobile robots, and in particular to a mobile robot, a positioning method thereof, and a computer-readable storage medium.

Background technique

When a mobile robot is working, it needs to be positioned. In the prior art, the positioning technology of the mobile robot mainly uses Monte Carlo positioning, and the Monte Carlo positioning is used for positioning by scattering particles. However, when a mobile robot performs Monte Carlo positioning, it usually locates the particles on the global map. The number of particles scattered globally is large, resulting in a large number of particles calculated by the mobile robot, which causes the mobile robot to consume more computing resources. The calculation rate is low, resulting in low positioning efficiency of the mobile robot.

Technical solutions

The main purpose of this application is to provide a mobile robot and its positioning method and computer readable storage medium, aiming to solve the problem of low positioning efficiency of the mobile robot.

In order to achieve the above objective, this application provides a positioning method of a mobile robot. The positioning method of the mobile robot includes the following steps:

Determine the first area where the mobile robot is located, and scatter particles in the first area to perform Monte Carlo positioning;

If positioning failure is detected, particles are scattered in the second area where the mobile robot is located for Monte Carlo positioning, wherein the area of the first area is smaller than the area of the second area, and the mobile robot is in the second area. The number of particles scattered in one area is less than the number of particles scattered in the second area by the mobile robot.

In an embodiment, the positioning method of the mobile robot further includes:

It is detected that the mobile robot starts to work, and the memory map of the mobile robot is acquired;

Determining the current pose of the mobile robot according to the memory map;

When it is determined according to the current pose that the mobile robot is not in a charging pile, the step of determining the first area where the mobile robot is located is executed.

In an embodiment, after the step of determining the current pose of the mobile robot according to the memory map, the method further includes:

When it is determined that the mobile robot is in the charging pile according to the current pose, perform ICP relocation;

After determining that the positioning fails, the step of determining the first area where the mobile robot is located is performed.

In an embodiment, after the step of spraying particles in the first area to perform local Monte Carlo positioning, the method further includes:

After confirming that the positioning is successful, perform ICP relocation;

After determining that the positioning fails, perform the step of scattering particles in the second area where the mobile robot is located to perform Monte Carlo positioning.

In an embodiment, after the step of scattering particles in the second area where the mobile robot is located for global Monte Carlo positioning, the method further includes:

After determining that the positioning is successful, perform ICP relocation.

In an embodiment, after determining that the positioning is successful, the pose of the mobile robot is determined, so as to determine a walking route according to the pose, and control the mobile robot to move along the walking route. In an embodiment, after the step of spraying particles in the second area where the mobile robot is located for Monte Carlo positioning, the method further includes:

After determining that the positioning fails, determine whether the second area is a global area;

When it is determined that the second region is a global region, the pose corresponding to the pose of the particle with the highest score in the second region is used as the pose of the mobile robot.

In an embodiment, after the step of determining whether the second area is a global area, the method further includes:

When it is determined that the second area is not a global area, particles are scattered in a third area where the mobile robot is located for Monte Carlo positioning, wherein the area of the second area is smaller than the area of the third area, and The number of particles scattered by the mobile robot in the second area is less than the number of particles scattered by the mobile robot in the third area.

To achieve the above objective, the present application also provides a mobile robot, the mobile robot including a memory, a processor, and a positioning program of the mobile robot stored in the memory and running on the processor. When the positioning program is executed by the processor, each step of the positioning method of the mobile robot as described above is realized.

To achieve the above objective, the present application also provides a computer-readable storage medium, the computer-readable storage medium includes a positioning program of the mobile robot, and the positioning program of the mobile robot is executed by a processor to realize the mobile robot as described above The various steps of the positioning method.

In the mobile robot and its positioning method and computer-readable storage medium provided in the present application, the mobile robot first determines the first area, sprays particles in the first area for Monte Carlo positioning, and after determining that the positioning fails, sprays particles in the second area Monte Carlo positioning, because the area of the first area is smaller than the area of the second area, and the number of particles scattered in the first area is less than the number of particles scattered in the second area, that is, the mobile robot first spreads a smaller number in a small area After the positioning fails, a larger number of particles are scattered in a larger area for positioning, which prevents the mobile robot from directly using more particles in the global area for positioning when positioning, which improves the positioning efficiency of the mobile robot .

Description of the drawings

FIG. 1 is a schematic diagram of the hardware architecture of a mobile robot involved in an embodiment of the application;

2 is a schematic flowchart of a first embodiment of a positioning method for a mobile robot according to this application;

3 is a schematic flowchart of a second embodiment of a positioning method for a mobile robot according to this application;

4 is a schematic flowchart of a third embodiment of a positioning method for a mobile robot according to this application.

The realization, functional characteristics, and advantages of the purpose of this application will be further described in conjunction with the embodiments and with reference to the drawings.

Implementation of this application

It should be understood that the specific embodiments described here are only used to explain the application, and are not used to limit the application.

The main solution of the embodiment of the present application is: determine the first area where the mobile robot is located, and spray particles in the first area to perform Monte Carlo positioning; after the positioning fails, in the second area where the mobile robot is located Sprinkle particles for Monte Carlo positioning, wherein the area of the first area is smaller than the area of the second area, and the number of particles sprinkled by the mobile robot in the first area is less than that of the mobile robot in the first area. The number of particles scattered in the second area.

Since the mobile robot first sprinkles a smaller number of particles in a small area for positioning, after the positioning fails, it sprinkles a larger number of particles in a larger area for positioning, avoiding the mobile robot directly using the global area when positioning. More particles are used for positioning, which improves the positioning efficiency of the mobile robot.

As an implementation scheme, the mobile robot can be as shown in Figure 1.

The solution of the embodiment of the present application relates to a mobile robot, and the mobile robot includes a processor 101, such as a CPU, a memory 102, and a communication bus 103. Among them, the communication bus 103 is used to implement connection and communication between these components.

The memory 102 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a magnetic disk memory. As shown in Fig. 1, the memory 103 as a computer storage medium may include a positioning program of the mobile robot; and the processor 101 may be used to call the positioning program of the mobile robot stored in the memory 102 and perform the following operations:

After determining that the positioning fails, particles are scattered in the second area where the mobile robot is located for Monte Carlo positioning, wherein the area of the first area is smaller than the area of the second area, and the mobile robot is in the first area. The number of particles scattered in the area is less than the number of particles scattered in the second area by the mobile robot.

In an embodiment, the processor 101 may be used to call the positioning program of the mobile robot stored in the memory 102 and perform the following operations:

After determining that the mobile robot starts to work, acquire the memory map of the mobile robot;

Determining the current pose of the mobile robot according to the memory map;

After the positioning failure is detected, the step of determining the first area where the mobile robot is located is executed.

After confirming that the positioning is successful, perform ICP relocation;

After detecting the positioning failure, perform the step of scattering particles in the second area where the mobile robot is located to perform Monte Carlo positioning.

After determining that the positioning is successful, perform ICP relocation.

After determining that the positioning is successful, determine the pose of the mobile robot to determine a walking route according to the pose, and control the mobile robot to move according to the walking route. In an embodiment, the processor 101 may be used to call the positioning program of the mobile robot stored in the memory 102 and perform the following operations:

After detecting the positioning failure, determine whether the second area is a global area;

When the second region is a global region, the pose corresponding to the pose of the particle with the highest score in the second region is used as the pose of the mobile robot.

When it is detected that the second area is not a global area, particles are scattered in the third area where the mobile robot is located to perform Monte Carlo positioning, wherein the area of the second area is smaller than the area of the third area, and The number of particles scattered by the mobile robot in the second area is less than the number of particles scattered by the mobile robot in the third area.

In this embodiment, according to the above-mentioned solution, the mobile robot first determines the first area, sprays particles in the first area to perform Monte Carlo positioning, and after determining that the positioning fails, sprays particles in the second area to perform Monte Carlo positioning. The area is smaller than the area of the second area, and the number of particles scattered in the first area is less than the number of particles scattered in the second area, that is, the mobile robot first sprays a smaller number of particles in a small area for positioning. After determining that the positioning fails, Then, a larger number of particles are scattered in a larger area for positioning, so as to avoid the mobile robot directly adopting more particles in the global area for positioning when positioning, which improves the positioning efficiency of the mobile robot.

Based on the above hardware architecture of the mobile robot, an embodiment of the positioning method of the mobile robot of the present application is proposed.

Referring to Fig. 2, Fig. 2 is a first embodiment of a positioning method of a mobile robot according to this application. The positioning method of a mobile robot includes the following steps:

Step S10: Determine the first area where the mobile robot is located, and spray particles in the first area to perform Monte Carlo positioning;

In this embodiment, the execution subject is a mobile robot, and the mobile robot may be a robot that can move by itself, such as a sweeping robot. When a mobile robot is working, it needs to be positioned. When positioning, the mobile robot uses its own pose as the base point to determine the first area. For example, it can use its own pose as the center to determine the first area. The area of the first area can be 4×4, and the unit can be cm, dm, or m, that is, 4cm×4cm, 4dm×4dm, or 4m×4m, which is not limited. It should be noted that the area of the first area is smaller than the area where the mobile robot is currently located. For example, the area where the mobile robot is located is the bedroom, and the area of the area currently located is the area of the bedroom. The area of the first area can be based on The area of the area where the mobile robot is currently located is flexibly set, that is, it only needs to ensure that the area of the first area is smaller than the area of the area where the mobile robot is currently located.

Step S20: After determining that the positioning fails, spray particles in the second area where the mobile robot is located to perform Monte Carlo positioning, wherein the area of the first area is smaller than the area of the second area, and the mobile robot is in the second area. The number of particles scattered in the first area is less than the number of particles scattered in the second area by the mobile robot.

After determining that the mobile robot determines that the positioning fails, the second area is further determined. The area of the second area is larger than the area of the second area. For example, if the area of the first area is 4dm×4dm, then the area of the second area may be 8dm×8dm. The area of the second area is less than or equal to the area of the area where the mobile robot is currently located.

After determining the second area, the mobile robot scatters particles in the second area for Monte Carlo positioning. The area of the second area is larger than the area of the first area. Therefore, the number of particles scattered by the mobile robot in the second area is more than that in the mobile robot. The number of particles scattered in the first area.

In addition, after determining the first area and the second area, the mobile robot will determine the obstacles in the first area and the second area. The first area and the second area can exist in the form of images, and the obstacles are in the first area. And the color of the image corresponding to the second area is black, the color of the non-obstacle area is white in the image, and the mobile robot only scatters particles in the area where the color is white.

It should be noted that determining whether the Monte Carlo positioning is successful is common knowledge of those skilled in the art, and will not be repeated here.

In the technical solution provided by this embodiment, the mobile robot first determines the first area, sprays particles in the first area to perform Monte Carlo positioning, and after determining that the positioning fails, sprays particles in the second area to perform Monte Carlo positioning. The area of one area is smaller than the area of the second area, and the number of particles scattered in the first area is less than the number of particles scattered in the second area, that is, the mobile robot first sprinkles a smaller number of particles in a small area to determine the positioning After the failure, a larger number of particles are scattered in a larger area for positioning, which prevents the mobile robot from directly using more particles in the global area for positioning when positioning, and improves the positioning efficiency of the mobile robot.

Referring to Fig. 3, Fig. 3 is a second embodiment of the positioning method of a mobile robot of this application. Based on the first embodiment, the positioning method of the mobile robot further includes:

Step S30, after determining that the mobile robot starts to work, acquire a memory map of the mobile robot;

Step S40: Determine the current pose of the mobile robot according to the memory map;

Step S50, when it is determined that the mobile robot is not in the charging pile according to the current pose, execute the step of determining the first area where the mobile robot is located, and scattering particles in the first area to perform Monte Carlo positioning;

Step S60, when it is determined that the mobile robot is in the charging pile according to the current pose, perform ICP relocation;

In step S70, after the positioning failure is detected, the step of determining the first area where the mobile robot is located is performed, and particles are scattered in the first area to perform Monte Carlo positioning.

In this embodiment, the mobile robot stores a memory map. When the mobile robot starts to work, the current pose of the mobile robot can be determined according to the memory map, and then it is determined whether the current pose of the mobile robot is a charging seat. It should be noted that pose refers to position and heading.

When the mobile robot is in the charging base, it can use ICP relocation for positioning. The mobile robot stores the ICP algorithm. The mobile robot uses the ICP algorithm to perform ICP relocation. The ICP algorithm calculates the relative pose transformation relationship between the two frames by matching the adjacent frames of the laser point cloud. Because the ICP algorithm only uses the phase Adjacent frames make the positioning efficiency of ICP relocation higher than that of Monte Carlo.

When the mobile robot starts to work on the charging stand, it performs ICP relocation. After determining that the positioning is successful, it will work according to the positioning pose. When the positioning fails, the mobile robot will determine the first area to perform Monte Carlo positioning. . When it is determined that the mobile robot is not in the charging base, that is, the mobile robot is at the stop or pause point after the last work, the mobile robot directly determines the first area to perform Monte Carlo positioning.

It should be noted that it is common knowledge of those skilled in the art to determine whether the ICP relocation is successful, and will not be repeated here.

In the technical solution provided by this embodiment, when the mobile robot is working, it is determined whether the current pose of the mobile robot is a charging stand according to the memory map. If so, ICP relocation is performed, because the positioning efficiency of ICP relocation is higher than Monte Carlo Luo’s positioning efficiency further improves the positioning efficiency of the mobile robot.

In one embodiment, after the mobile robot scatters particles in the first area for Monte Carlo positioning, after determining that the positioning is successful, ICP relocation is required for secondary confirmation; of course, the mobile robot scatters particles in the second area. After Monte Carlo positioning, after confirming that the positioning is successful, ICP repositioning is also required for secondary confirmation. It is understandable that after the Monte Carlo positioning of the mobile robot is successful, ICP repositioning is required for secondary confirmation, thereby improving the accuracy of mobile robot positioning.

It should be noted that when the mobile robot performs Monte Carlo positioning, the mobile robot is mobile, that is, the posture of the ICP relocation performed after the Monte Carlo positioning is successful does not coincide with the posture of the charging stand. , The positioning result of the ICP relocation performed on the charging base is not necessarily the same as the positioning result of the ICP relocation performed after the Monte Carlo positioning is successful, and the positioning result is the positioning success or the positioning failure.

In one embodiment, after determining that the positioning is successful, that is, the ICP relocation is successful, the Monte Carlo positioning corresponding to the first area is successful, or the Monte Carlo positioning corresponding to the second area is successful, the mobile robot determines the pose, and then determines the pose according to the position. The posture determines the walking route, so that the mobile robot moves according to the walking route. After determining that the mobile robot is a sweeping robot, the walking route is the sweeping route.

Referring to Fig. 4, Fig. 4 is a third embodiment of a positioning method for a mobile robot according to this application. Based on the first or second embodiment, after the step S20, the method further includes:

Step S80, after determining that the positioning fails, determine whether the second area is a global area;

Step S90: When it is determined that the second region is a global region, the pose corresponding to the pose of the particle with the highest score in the second region is used as the pose of the mobile robot.

Step S100: When it is determined that the second area is not a global area, particles are scattered according to the third area where the mobile robot is located for Monte Carlo positioning, wherein the area of the second area is smaller than the area of the third area, And the number of particles scattered by the mobile robot in the second area is less than the number of particles scattered by the mobile robot in the third area.

In this embodiment, the mobile robot is provided with multiple regions, and the area of each region increases in sequence, and the area of the largest region is the area of the region where the mobile robot is currently located. The mobile robot performs Monte Carlo positioning in the first area. After the positioning fails, it performs Monte Carlo positioning in the second area, and so on, until the mobile robot performs Monte Carlo positioning on the area with the largest area, that is, the mobile robot global Map for positioning.

In this regard, after the mobile robot determines that the Monte Carlo positioning corresponding to the second area fails, it determines whether the second area is a global area, that is, whether the second area is the area with the largest area, and if not, it performs the third area Monte Carlo positioning, the area of the third area is larger than the area of the second area, and the number of particles scattered by the mobile robot in the third area is more than the number of particles scattered by the mobile robot in the second area. After determining that the second region is the global region, the pose corresponding to the pose of the particle with the highest score in the second region is taken as the pose of the mobile robot.

It should be noted that in this embodiment, the second area is used to distinguish it from the first area. The first and second areas do not indicate the number of areas. It should be understood that the first area can be used by a mobile robot to perform the third The Monte Carlo positioning of each area may also be the Monte Carlo positioning of the fourth area performed by the mobile robot.

In addition, in the foregoing embodiment, after it is determined that ICP relocation is required for successful positioning, and after ICP relocation fails, Monte Carlo positioning of the next larger area is performed.

In the technical solution provided in this embodiment, the mobile robot is provided with multiple regions, and after the second region fails to locate, Monte Carlo positioning of the third region whose area is larger than the second region is performed to ensure that the mobile robot can successfully locate.

The application also provides a mobile robot including a memory, a processor, and a positioning program of the mobile robot stored in the memory and running on the processor, and the positioning program of the mobile robot is When the processor is executed, each step of the positioning method of the mobile robot described in the above embodiment is realized.

The present application also provides a computer-readable storage medium, the computer-readable storage medium includes a positioning program of a mobile robot, and the positioning program of the mobile robot is executed by a processor to realize the positioning method of the mobile robot as described in the above embodiment The various steps.

The serial numbers of the foregoing embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, It also includes other elements not explicitly listed, or elements inherent to the process, method, article, or device. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article or device that includes the element.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better.的实施方式。 Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disk, optical disk), including several instructions to make a terminal device (can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the method described in each embodiment of the present application.

The above are only preferred embodiments of this application, and do not limit the scope of this application. Any equivalent structure or equivalent process transformation made using the content of the description and drawings of this application, or directly or indirectly used in other related technical fields , The same reason is included in the scope of patent protection of this application.

Claims

A positioning method of a mobile robot, wherein the positioning method of the mobile robot includes the following steps:

Determine the first area where the mobile robot is located, and scatter particles in the first area to perform Monte Carlo positioning;

After detecting the positioning failure, particles are scattered in the second area where the mobile robot is located to perform Monte Carlo positioning, wherein the area of the first area is smaller than the area of the second area, and the mobile robot is in the The number of particles scattered in the first area is less than the number of particles scattered in the second area by the mobile robot.
The positioning method of a mobile robot according to claim 1, wherein the positioning method of the mobile robot further comprises:

It is detected that the mobile robot starts to work, and the memory map of the mobile robot is acquired;

Determining the current pose of the mobile robot according to the memory map;

When it is determined according to the current pose that the mobile robot is not in a charging pile, the step of determining the first area where the mobile robot is located is executed.
The positioning method of a mobile robot according to claim 2, wherein after the step of determining the current pose of the mobile robot according to the memory map, the method further comprises:

When it is determined that the mobile robot is in the charging pile according to the current pose, perform ICP relocation;

After determining that the ICP positioning fails, perform the step of determining the first area where the mobile robot is located.
The positioning method of a mobile robot according to claim 1, wherein after the step of scattering particles in the first area to perform local Monte Carlo positioning, the method further comprises:

After confirming that Monte Carlo positioning is successful, perform ICP relocation confirmation;

After it is determined that the Monte Carlo positioning fails, the step of scattering particles in the second area where the mobile robot is located to perform Monte Carlo positioning is performed.
The method for positioning a mobile robot according to claim 1, wherein after the step of scattering particles in the second area where the mobile robot is located for global Monte Carlo positioning, the method further comprises:

After confirming that the Monte Carlo positioning is successful, perform ICP relocation confirmation.
The positioning method of a mobile robot according to any one of claims 1 to 5, wherein after the positioning is successful, the pose of the mobile robot is determined, so as to determine the walking route according to the pose and control the movement The robot moves according to the walking route.
The positioning method of a mobile robot according to any one of claims 1 to 5, wherein after the step of spraying particles in the second area where the mobile robot is located for Monte Carlo positioning, the method further comprises:

After determining that the positioning fails, determine that the second area is a global area;

When it is determined that the second region is a global region, the pose corresponding to the pose of the particle with the highest score in the second region is used as the pose of the mobile robot.
8. The positioning method of a mobile robot according to claim 7, wherein after the step of determining the second area as a global area, the method further comprises:

When it is determined that the second area is not a global area, particles are scattered in a third area where the mobile robot is located for Monte Carlo positioning, wherein the area of the second area is smaller than the area of the third area, and The number of particles scattered by the mobile robot in the second area is less than the number of particles scattered by the mobile robot in the third area.
A mobile robot, wherein the mobile robot includes a memory, a processor, and a positioning program of the mobile robot stored in the memory and running on the processor, and the positioning program of the mobile robot is controlled by the processor. When executed, each step of the positioning method of a mobile robot according to any one of claims 1-8 is realized.
A computer-readable storage medium, wherein the computer-readable storage medium includes a positioning program of a mobile robot, and the positioning program of the mobile robot is executed by a processor to realize the movement according to any one of claims 1-8. The steps of the robot positioning method.