WO2022252221A1

WO2022252221A1 - Mobile robot queue system, path planning method and following method

Info

Publication number: WO2022252221A1
Application number: PCT/CN2021/098376
Authority: WO
Inventors: 鲁守银; 张强; 高诺; 张涛; 高焕兵; 王涛
Original assignee: 山东建筑大学
Priority date: 2021-05-31
Filing date: 2021-06-04
Publication date: 2022-12-08
Also published as: CN113190020A

Abstract

Disclosed in the present invention are a mobile robot queue system, a path planning method and a following method. The system comprises a plurality of robots and an upper computer, wherein each robot communicates with the upper computer by means of a first communication module, and the robots communicate with each other by means of second communication modules; the upper computer can designate any one or more robots to be a pilot robot(s), and the remaining mobile robots to be following robots, the pilot robot performing path planning according to environment information which is obtained by means of a sensing module carried thereby and the second communication module, and each following robot obtaining the location relationship between itself and the pilot robot by means of a positioning module carried thereby, so as to realize following; and the upper computer sets the distance between the pilot robot and each following robot, so as to change the formation of the pilot robot and the following robots.

Description

A mobile robot queuing system and path planning and following method

technical field

The invention belongs to the field of multi-robot path planning and obstacle avoidance, and mainly relates to a method for moving path planning and obstacle avoidance of a robot queue, which is mainly used in the medical field, military operations, industrial production and post-disaster reconstruction.

Background technique

In recent years, in some applications such as industrial production and post-disaster reconstruction, the efficient work of robot queues has attracted people's attention, and the prospect of robot queues has become brighter, but there are still many problems in the application process.

First of all, the synchronization of mobile robot queues during operation is the key issue of research. Synchronization is the basis for realizing robot queues. Common methods include behavior-based methods, pilot-following methods, and virtual structure methods. For example: CN201310402941.3 discloses a multi-mobile robot control system based on following the leader formation, including an experimental environment image acquisition module, a host computer positioning module, a vehicle-type mobile robot group, a communication module, and a control algorithm module. Wherein the experimental environment image acquisition module will be used to collect video images of a plurality of mobile robot formation experimental environments; the upper computer positioning module uses image processing algorithms to calculate the absolute position of each robot in real time through the coordinate system calibrated by the camera Information; the car-type mobile robot group is composed of multiple single mobile cars, and independently decides to complete the formation task; the communication module performs data interaction and information sharing through wireless communication; the control algorithm module is based on the pilot follow The formation algorithm coordinates and controls the entire system to complete the formation task. But this system has the following problems:

The system uses industrial cameras to obtain robot image information to obtain the pose of the robot. The application conditions are harsh, and the accuracy of the obtained pose information is not enough. The system can only be used under special indoor conditions, and cannot be used outdoors and long-distance operations, which has great limitations.

Secondly, the mobile robot needs to find the optimal path in the process of reaching the target point. The traditional path planning of the mobile robot regards the mobile robot as a particle for analysis, while the mobile robot queue is the march of multiple targets, which requires the entire The robot queue moves synchronously; the problems in this way are:

The robot queue must maintain the formation during the movement, and the path planning of a single robot cannot maintain the formation during the movement. For obstacles whose volume is smaller than the queue spacing, it is easy for the robot to avoid obstacles, and the robot queue should also be able to pass smoothly.

Finally, when the mobile robot queue faces obstacles and emergencies during operation, it needs to maintain the robot queue while avoiding obstacles. For example, in the patent CN201310402941.3, a fuzzy formation and avoidance Firstly, the leading robot detects whether there is an obstacle in the forward area; if there is no obstacle, it will continue to run in the original formation; if there is, the multi-mobile robot system enters the obstacle avoidance state, and then informs all following robots in the form of broadcast ;Finally, the follower robot switches formations according to the stored information of different formations and the information broadcast by the leading robot, and determines its position in the formation; repeat the above process. The invention adopts the fuzzy formation and obstacle avoidance control method to realize the multi-mobile robot formation function in an unknown environment, and can effectively avoid obstacles to run. However, this method adopts a method based on a pilot robot, which mainly relies on a fully functional robot as the pilot robot, and the host computer cannot effectively monitor and control the robot queue. When the leader robot fails, it will cause errors in the queue, and when the leader robot cannot work, the entire queue will also be unable to work. Therefore, the reliability and stability of this method are poor, and it cannot cope with complex environments and unexpected situations.

Contents of the invention

The technical problem mainly solved by the present invention is to propose a method for path planning and obstacle avoidance of the mobile robot queue, which can keep the mobile robot queue moving synchronously, and the movement of each individual is not affected, and can also realize the robot queue At the same time, obstacles on the path can be effectively avoided during the travel process, reducing the loss of the robot.

In order to solve the above problems, the technical solution adopted in the present invention is:

In the first aspect, for the queue problem of mobile robots, the present invention proposes a mobile robot queue system based on multi-sensors; including a host computer and a plurality of robots, each robot communicates with the host computer through the first communication module; The robots communicate with each other through the second communication module; the host computer can designate any one or more robots as the leader robot, and the rest of the mobile robots as follower robots; The environmental information obtained by the second communication module performs path planning; the following robot obtains the positional relationship between itself and the pilot robot through the positioning module carried by itself, and realizes following; The distance between the leader robot and the follower robot can realize the formation transformation.

In the present invention, a positioning module and a wireless communication module are installed on each mobile robot, and one mobile robot is designated as a pilot robot, and the rest of the mobile robots are used as follower robots. The positional relationship with the pilot robot is to follow the pilot robot by maintaining the set following distance position with the pilot robot. At the same time, different formations can be realized by setting parameters such as the position distance of the follower robot relative to the leader robot, so as to meet actual needs. And the setting of the pilot robot can not be unique, but generally only one is enough. In complex environments, multiple pilot robots can be set to improve the stability of the system.

In the second aspect, the present invention also proposes a path planning method based on a multi-sensor mobile robot queue system. When the mobile robot queue is working, the upper computer first sets the formation formation and determines the leader robot, and sends it to the mobile robot through the wireless communication module. Mobile robot, after receiving instructions, the mobile robot follows the robot to the designated location. The surrounding obstacle information is detected by the panoramic camera and the ultrasonic sensor, and the following robot transmits the obstacle information to the pilot robot through the Wi-Fi communication module, and the pilot robot performs path planning and starts to move. Include the following steps:

Step 1. Any robot obtains the command from the host computer and acts as a leader robot; the other robots acquire commands from the host computer as follower robots, and follow the robots to move to the specified position to form a robot queue;

Step 2, the pilot robot collects information on obstacles in the environment;

Step 3, the pilot robot obtains the relative position information of the obstacle collected by the follower robot;

Step 4, the pilot robot applies all obstacle position information to the grid map;

Step 5, take the current position of the pilot robot as the initial position, and take the final position as the target position;

Step 6, randomly generating a random point X _rand in the grid map;

Step 7, find the nearest X _near to X _rand among the points of the known tree;

Step 8, intercept point X _new with step size m from X _near to X _rand direction;

Step 9, if there is no obstacle between X _near and X _new , find an alternative parent node of X _near with a fixed radius L around X _near ;

Step 10, calculate the path from the starting point to each candidate parent node and then to X _new , and find out the candidate parent node with the shortest path as the reselected parent node of X _new ;

Step 11, calculate the nodes with X _new as the center and L as the radius, if the distance from the starting point to X _new and then to the surrounding nodes is shorter than the distance from the starting point to the surrounding nodes of X _new , then take X _new as the parent of the surrounding nodes node;

Step 12, add X _new to the collection of trees, and return to step 6;

Step 13, when growing to the target point, select the path with the shortest distance as the optimal path for planning.

In the third aspect, the present invention also provides a robot following method. During the operation of the robot queue, the pilot robot first starts to work, and the follower robot follows. Each mobile robot is equipped with a Wi-Fi communication module that can communicate with each other. The pilot robot detects its own position information through the GPS module, and then transmits the position information to the follower robot through the Wi-Fi communication module. The follower robot uses the pilot robot The location information to follow, the specific steps are as follows:

Follow the robot to obtain the location information of the pilot robot in real time;

Establish a following robot kinematics model in the following robot;

Introduce the pose error in the kinematics model of the following robot to obtain the following motion model of the following robot;

The sensor on the following mobile robot collects the current displacement linear velocity and rotational angular velocity in real time and feeds them back to the control module of the following mobile robot. The control module of the following mobile robot performs calculations to obtain the trajectory tracking error, and then uses the trajectory tracking control method to control the following mobile robot. The trajectory of the robot is adjusted in real time to realize the follow-up of the pilot robot.

Further, when obstacles are encountered during the operation of the robot queue, obstacle avoidance must be performed. When the sensor of the lead robot detects that the distance from the obstacle to the lead robot is d1, it will decelerate immediately, and the follower robot will also decelerate. After leaving the obstacle, the lead robot and the follower robot will accelerate to the original speed. When the sensor of the leading robot detects that the distance from the obstacle to the leading robot is d2, it immediately decelerates until it stops, and at the same time the following robot stops to the following position.

The mobile robot detects obstacle information and re-plans the path.

Step 3.4, when the sensor of the following robot detects that the distance from the obstacle to the leading robot is d1, decelerate immediately, and accelerate to the following position after leaving the obstacle; when the sensor of the leading robot detects that the distance from the obstacle to the leading robot is d2, immediately Slow down until it stops, send a message to the leader robot, the leader robot stops moving, and the follower robot plans a path to the following position. When the follower robot arrives, the robot queue starts to move.

In step 3.5, after the robot queue stops moving, use the GPS positioning device to detect the current position information, and return to step 3.3 if the target point is not reached.

The ultrasonic sensors installed on the car body of each mobile robot can detect the surrounding obstacle information in real time. When the robot is moving, a stop area d2 and a deceleration area d1 are set at a certain distance around it. The settings of the deceleration area d1 and the stop area d2 are related to the current speed, pose and body size of the mobile robot. When the vehicle speed is relatively high, the range of d1 and d2 is relatively large.

When the robot queue arrives at the destination and needs to be docked or needs to change formation, the host computer transmits to the lead robot and the follower robot through the wireless communication module, and the follower robot moves to a new follow position after receiving the command.

The beneficial effects of the present invention are as follows:

(1) The present invention uses a plurality of sensors as the environment perception system of the robot, which can effectively detect its own running state and environment information, and improve the adaptability of the system in complex environments.

(2) The present invention adopts the rapid expansion random tree method for path planning, and superimposes the environmental information of each robot on the pilot robot for planning, which not only improves the efficiency of path planning, but also ensures the normal movement of a single robot.

(3) The upper computer of the present invention can monitor the operating status of the system in real time and issue instructions to the system. Each robot can be used as a pilot robot, and the pilot robot and formation can be set at any time through the host computer to cope with different environments and needs.

Description of drawings

Fig. 1 is the schematic diagram of mobile robot formation;

Fig. 2 is a block diagram of the robot system;

Fig. 3 is the flow chart of mobile robot formation transformation;

Fig. 4 is the flow chart of mobile robot queue path planning;

Figure 5 is a flow chart of mobile robot queue obstacle avoidance.

Detailed ways

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

It should be noted that the terminology used here is only for describing specific embodiments, and is not intended to limit exemplary embodiments according to the present invention. As used herein, unless the invention clearly states otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, their Indicate the presence of features, steps, operations, means, components and/or combinations thereof;

Below in conjunction with accompanying drawing this patent is described:

The schematic diagram of the mobile robot queue shown in Figure 1 is an application of this patent, including a pilot robot and a follower robot. Using the pilot robot method to control the mobile robot queue has the advantages of low cost and high stability. The number of following robots and the formation of the robot queue can be adjusted by setting the robot queue matrix through the host computer.

Figure 2 is a schematic diagram of the robot system, including a control module, a drive module, a perception module, a positioning module and a communication module; the control module is used as the core controller of the robot, and an embedded system is used. The core controller processes the perception module, the positioning module, The data of the communication module is used to control the operation of the drive module. After receiving the instructions from the control module, the drive module drives the motor or reducer to run, so as to realize the acceleration, deceleration and steering actions of the mobile robot.

Further, the above perception system is a module for the mobile robot to collect environmental information and its own information, and is composed of multiple sensors, including ultrasonic sensors, pose sensors, temperature sensors, power detection sensors and visual sensors; the visual sensors are installed on the mobile robot On the top of the car body, the information of environmental obstacles is scanned and sent to the control module. Ultrasonic sensors are installed in the four directions of the mobile robot body to assist in the detection of environmental information, and real-time detection of obstacle information is sent to the control module. The temperature sensor is installed on the motor and the outside of the robot to detect the motor temperature and ambient temperature in real time, and send the temperature information to the controller. When the temperature of the motor or the environment is too high, the control module sends a stop command to the drive module, and sends it to the host computer through the communication module. The power detection sensor is installed in the power supply part, and the remaining power of the mobile robot can be checked in real time through the host computer. The pose sensor is composed of an angle sensor, a gyroscope and an acceleration sensor. The angle sensor is installed in the steering part of the front wheel to detect the steering angle of the front wheel. The gyroscope and the acceleration sensor are installed inside the mobile robot to detect the gap between the robot's current longitudinal axis and the x-axis. angle and acceleration.

The positioning module uses a GPS positioning device to obtain the position coordinates of the center point of the mobile robot, so as to determine the position of the mobile robot. The positioning module sends the collected position information to the control module for processing, and controls the communication module to transmit information.

The communication module includes the wireless communication module between the mobile robot and the upper computer, and the Wi-Fi communication module between the mobile robots. The control module controls the communication module to send information, and the communication module sends the received information to the control module for processing. Through the wireless communication module, the user can know the running status of all robots in real time. When a mobile robot fails and cannot continue to work, or when the communication fails, the communication module sends it to the host computer for processing.

The above-mentioned multiple sensors send the collected information to the control module, and the control module controls the drive module to respond, and at the same time sends it to the host computer in real time through the communication module.

In this embodiment, the number of following robots is set to 2, and their following positions are (-1,-1) and (1,-1) respectively. According to the schematic diagram of the robot queue flow in Figure 3, the formation matrix _P1 can be obtained as:

First determine the number of following robots and the formation of mobile robots, and input the formation matrix P ₁ through the host computer.

The host computer transmits instructions to the mobile robot through the wireless communication module, and the pilot robot collects its own location information through the GPS positioning module, and transmits the collected location information to the follower robot through the Wi-Fi communication module.

After the following robot receives the position information of the leading robot through the Wi-Fi communication module, it determines its own position through the GPS positioning module, and then determines the walking path through path planning.

The following robot sends instructions to the driving module through the control module, and the driving module drives the motor to run, so that the following robot reaches the designated following position to form a robot queue.

Fig. 4 is a flow chart of the route planning of the mobile robot queue in the present invention. In this embodiment, the follower robot detects the surrounding environment through its own panoramic camera and ultrasonic sensor, grids the environment, and subdivides the environment into a unit , and binarize it, set the position with obstacles to 1, and the position without obstacles to 0. The detected relative position obstacle information is transmitted to the controller of the pilot robot through the Wi-Fi communication module.

The pilot robot receives the obstacle information of the relative position of the following robot through the communication module, and the control module superimposes the obstacle information of the relative position of the following robot on the obstacle information of the pilot robot to establish the obstacle environment information.

The steps of robot queue path planning are as follows:

Step 1.1, take the current position of the pilot robot as the initial point, and take the final position as the target point.

In step 1.2, a random point X _rand is randomly generated in the grid map.

Step 1.3, find the nearest X _near to X _rand among the points of the known tree in the grid map.

Step 1.4, intercept point X _new with step m in the direction from X _near to X _rand .

Step 1.5, _if there is no obstacle between X _near and X _new , find an alternative parent node of X near with a fixed radius L around X _near .

Step 1.6, calculate the path from the starting point to each candidate parent node and then to X _new , and find out the candidate parent node with the shortest path as the reselected parent node of X _new .

Step 1.7, calculate the nodes with X _new as the center and L as the radius, if the distance from the starting point to X _new and then to the surrounding nodes is shorter than the distance from the starting point to the surrounding nodes of X _new , then use X _new as the parent of the surrounding nodes node.

Step 1.8, add X _new to the collection of trees. Meanwhile return to step 1.2.

Step 1.9, when growing to the target point, select the path with the shortest distance as the optimal path for planning.

The mobile robot sends its own running status to the host computer in real time, and the user can monitor the running status of the mobile robot in real time through the host computer.

After the pilot robot moves, the position information (x, y) is collected in real time through the GPS positioning module, and sent to the following robot through the Wi-Fi module. After receiving the information, the Wi-Fi module of the following robot sends it to the control module for trajectory tracking processing. Make the follower robot follow the lead robot in real time.

The main steps to follow the robot trajectory tracking are as follows:

The follower robot obtains the location information of the lead robot in real time, that is, the lead robot starts to work and transmits the location information to the follower robot in real time

Establish a following robot kinematics model in the following robot;

Establish the following robot kinematics model as follows:

Where x(t), y(t) are the position coordinates of the following robot at time t, and θ(t) is the deflection angle of the following robot's motion direction relative to the X axis at time t.

and

are the first derivatives of x(t), y(t), θ(t) and v(t), respectively. v(t) represents the linear velocity fed back by the robot sensor,

Indicates the front wheel angle, L indicates the length of the car body, and a indicates the acceleration of the mobile robot.

The position information of the pilot robot consists of x _o (t), y _o (t) and θ _o (t), which are the coordinates of the pilot robot in Cartesian coordinates and the deflection angle relative to the X axis. Through the composition of the queue, the position information of the follower robot relative to the leader robot can be obtained as x _r (t), y _r (t) and θ _r (t), so the target position of the follower robot is x _r (t), y _r (t) and _θr (t).

x _o (t), y _o (t) are measured by GPS sensor, θ _o (t) is measured by gyroscope,

Measured by the angle sensor.

On the basis of the above formula, the pose error is introduced as [x _e (t) y _e (t) θ _e (t)] ^T , and the coordinate transformation is as follows:

Among them, x _e (t), y _e (t) is the error between the actual position of the following robot and the expected distance in the X-axis direction and the error in the Y-axis direction at time t, and θ _e (t) is the relative movement direction of the following robot at time t. The deviation between the declination of the X axis and the desired position relative to the declination of the X axis.

Determine the current position information according to the GPS positioning module, determine the current position and orientation information according to the known map information and the environmental information collected by the sensor in real time, calculate the error between the expected position and the actual position of the following robot, and find out the control required for the mobile robot to follow The acceleration and front wheel angle are given by the control module, and the drive module drives the actuator to follow.

Further, obstacle avoidance is performed when the robot queue encounters an obstacle.

Fig. 5 is a flow chart of robot queue moving and avoiding obstacles.

The robot queue sets the necessary safety distance d1 _n and d2 _n during the operation process, which is controlled by the ultrasonic sensor on the mobile robot body in real time, and an ultrasonic sensor is installed on the front, rear, left, and right sides of each mobile robot body.

The numbers of the ultrasonic sensors are h ₁ , h ₂ , h ₃ and h ₄ , which represent four ultrasonic sensors, front, rear, left, and right respectively. Moving the ultrasonic sensors during operation detects the surrounding environment in real time.

When the mobile robot runs in a straight line, the _h1 sensor detects the obstacles ahead, and sets the deceleration distance d1 and the stop distance d2, and the distance between d1 and d2 increases with the increase of speed.

h ₂ detects obstacles behind the robot, and does not need to be set when the mobile robot is going straight.

h ₃ and h ₄ detect obstacles in the left and right directions of the robot, and only need to set the stop area d2 when the mobile robot is going straight to ensure the safe passage of the robot.

When the mobile robot turns, according to the front wheel steering angle

To set the safety distances d1 and d2 of the sensors _h3 and _h4 .

Step 3.1, when the ultrasonic sensor of the pilot robot detects that the distance from the obstacle to the pilot robot is d1, it will decelerate immediately, and at the same time send information to the following robot through the Wi-Fi communication module, and the following robot will also decelerate. After leaving the obstacle, the pilot robot and follow the robot to accelerate to the original speed.

Step 3.2, when the sensor of the leading robot detects that the distance from the obstacle to the leading robot is d2, it immediately decelerates until it stops, and at the same time the following robot stops to the following position.

In step 3.3, the mobile robot detects obstacle information and re-plans the path.

The method adopted by the invention has the advantages of high applicability, low cost, strong stability, etc., and can cope with various emergencies at the same time.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

A mobile robot queuing system, including a plurality of robots and a host computer, is characterized in that each robot communicates with the host computer through a first communication module; each robot communicates with each other through a second communication module; said The host computer can designate any one or more robots as the leader robot, and the rest of the mobile robots as follower robots; the leader robot performs path planning through the environmental information obtained by the perception module carried by itself and the second communication module; the follower robot The robot obtains the positional relationship between itself and the leader robot through the positioning module carried by itself, and realizes following; the host computer realizes the formation transformation between the leader robot and the follower robot by setting the distance between the leader robot and the follower robot.
The mobile robot queuing system according to claim 1, wherein each robot includes a control module, the input of the control module is connected to the perception module, the positioning module, the first communication module and the second communication module, and the output is connected to the drive module, a first communication module and a second communication module;

The drive module drives the robot to accelerate, decelerate and turn;

The perception module collects environmental information and its own information;

The positioning module is used to obtain the position coordinates of the center point of the mobile robot and determine the position of the mobile robot;

The first communication module is used for communication between the mobile robot and the host computer;

The second communication module is used for communication between mobile robots.
The mobile robot queuing system according to claim 1, wherein the perception module includes an ultrasonic sensor, a pose sensor, a temperature sensor, a power detection sensor and a vision sensor;

The vision sensor is installed on the body of the mobile robot to detect the information of environmental obstacles;

Ultrasonic sensors are installed in the four directions of the mobile robot body to assist in the detection of environmental information and obstacle information;

The temperature sensor is installed inside and outside the mobile robot to detect the motor temperature and the external air temperature respectively;

The power detection sensor is installed on the power supply of the robot to detect the power condition of the robot;

The pose sensor includes an angle sensor, a gyroscope and an acceleration sensor. The angle sensor is installed on the front wheel to measure the rotation angle of the front wheel; the gyroscope and the acceleration sensor are installed inside the robot to detect the attitude and acceleration of the mobile robot.
The path planning method of the mobile robot queuing system as described in any one of claims 1-3, it is characterized in that,

Step 1. Any robot obtains the command from the host computer and acts as a leader robot; the other robots acquire commands from the host computer as follower robots, and follow the robots to move to the specified position to form a robot queue;

Step 2, the pilot robot collects information on obstacles in the environment;

Step 3, the pilot robot obtains the relative position information of the obstacle collected by the follower robot;

Step 4, the pilot robot applies all obstacle position information to the grid map;

Step 5, take the current position of the pilot robot as the initial position, and take the final position as the target position;

Step 6, randomly generating a random point X rand in the grid map;

Step 7, find the nearest X near from X rand in the known tree points of the grid map;

Step 8, intercept point X new with step size m from X near to X rand direction;

Step 9, if there is no obstacle between X near and X new , find an alternative parent node of X near with a fixed radius L around X near ;

Step 10, calculate the path from the starting point to each candidate parent node and then to X new , and find out the candidate parent node with the shortest path as the reselected parent node of X new ;

Step 11, calculate the nodes with X new as the center and L as the radius, if the distance from the starting point to X new and then to the surrounding nodes is shorter than the distance from the starting point to the surrounding nodes of X new , then take X new as the parent of the surrounding nodes node;

Step 12, add X new to the collection of trees, and return to step 6;

Step 13, when growing to the target point, select the path with the shortest distance as the optimal path for planning.
The following method of the multi-sensor based mobile robot queue system according to any one of claims 1-3, wherein,

Follow the robot to obtain the location information of the pilot robot in real time;

Establish a following robot kinematics model in the following robot;

Introduce the pose error in the kinematics model of the following robot to obtain the following motion model of the following robot;

The sensor on the following mobile robot collects the current displacement linear velocity and rotational angular velocity in real time and feeds them back to the control module of the following mobile robot. The control module of the following mobile robot performs calculations to obtain the trajectory tracking error, and then uses the trajectory tracking control method to control the following mobile robot. The trajectory of the robot is adjusted in real time to realize the follow-up of the pilot robot.
The following method of the multi-sensor based mobile robot queuing system according to claim 5, characterized in that when the robot is moving, a stop area d2 and a deceleration area d1 are set at a certain distance around it.
The following method of the mobile robot queuing system based on multiple sensors as claimed in claim 6, wherein when the sensor of the pilot robot detects that the distance from the pilot robot to an obstacle is d1, the deceleration is performed, and the follower robot also decelerates simultaneously. After the obstacle, the lead robot and the following robot accelerate to the original speed; when the sensor of the lead robot detects that the distance from the lead robot to the obstacle is d2, it immediately decelerates until it stops, and at the same time the follower robot stops to the following position, and the mobile robot detects the information of the obstacle in the environment , and re-plan the path by the pilot robot.
The following method of the mobile robot queue system based on multi-sensors as claimed in claim 6, wherein when the sensor of the following robot detects that the distance from the obstacle to the leader robot is d1, it immediately decelerates, and when leaving the obstacle, it accelerates to reach Follow the position; when the sensor of the following robot detects that the obstacle is d2 away from the leading robot, it will immediately decelerate until it stops, send a message to the leading robot, the leading robot stops moving, and the following robot plans a path to reach the following position. When the following robot arrives, the robot queues Start to move; after the robot queue stops moving, use the positioning device to detect the current position information, and continue to move forward if it does not reach the target point.
The following method of the mobile robot queue system based on multi-sensors as claimed in claim 5, wherein when the robot queue arrives at the destination and needs to stop or needs to change formation, the host computer transmits the data to the pilot robot through the second wireless communication module And following the robot, the following robot moves to a new following position after receiving the instruction.