A mobile robot obstacle automatic avoidance and bypassing method

Abstract

The application discloses a kind of mobile robot obstacle automatic avoidance bypassing method, comprising: S1 obtains grid map;S2 whether there is obstacle in the route of advance is judged by multi-line laser radar device, and whether the obstacle and the path of mobile robot coincide is judged;S3 the virtual center point of obstacle is calculated;S4 the virtual radius of obstacle is calculated;S5 real-time updates the virtual radius of obstacle, if virtual radius becomes larger, then re-planning point position;The method can plan path in real time, and safety, detection accuracy is higher.

Description

Technical Field

[0001] The present invention belongs to the technical field of obstacle avoidance, and in particular relates to a method for automatically avoiding and circumventing obstacles for a mobile robot. Background Art

[0002] As society continues to evolve towards intelligence, intelligent robots are increasingly being used across various industries. Logistics companies are also turning their attention to warehouse automation and intelligentization. Research on routing algorithms for robotic carts within warehousing systems has practical implications for improving traditional logistics operations, increasing efficiency, and reducing errors in manual operations.

[0003] For intelligent robots, obstacles may appear during their moving path. If obstacle avoidance and path planning determine the driving efficiency of the intelligent robot, how to solve the common problems in this field such as unsatisfactory obstacle avoidance and inability to plan the optimal path when the operating environment of the robot car is relatively complex is an issue that technical personnel in this field urgently need to solve.

[0004] In order to solve the above problems, a patent document with Chinese patent application number 202110482260.7 and publication date of July 23, 2021, discloses an intelligent logistics path planning method and system. The method includes: collecting environmental information and establishing a map based on the collected environmental information; representing the map through a two-dimensional array and rasterizing the map; setting the robot's starting point, end point, speed change rate and the obstacle's starting point, end point, coordinate axis speed change, safety distance and threat distance; performing global path planning based on the A* algorithm combined with a heuristic function to obtain a global optimal path; according to the global optimal path, the robot performs dynamic obstacle judgment during movement. If a dynamic obstacle is encountered, the path is replanned. If no dynamic obstacle is encountered, the path planning is completed; the system includes: a map establishment module, a map preprocessing module, a map initialization module, a global path planning module and a local dynamic obstacle avoidance module. This patent can complete path planning from the starting point to the end point and automatically avoid dynamic obstacles during movement.

[0005] This method only uses the A* algorithm combined with a heuristic function for global path planning. When encountering an obstacle, it simply rescans the QR code at the current location to determine the current position and replan the path. It cannot dynamically predict obstacles before encountering them, which can effectively save avoidance time and ensure effective obstacle avoidance. However, it cannot guarantee the optimal avoidance path when encountering obstacles. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for automatically avoiding obstacles for a mobile robot. The method is based on whether the contour coordinates of the mobile robot on the planned path overlap with the virtual coordinates of the obstacle. If they overlap, a virtual radius is planned based on the virtual center of the obstacle and a safety point, and then a new path point is replanned to achieve avoidance. This method can plan the path in real time, and has higher safety and measurement accuracy.

[0007] To achieve the above-mentioned purpose, a method for automatically avoiding obstacles for a mobile robot is provided, comprising the following steps:

[0008] S1 uses a lidar device to obtain information about the surrounding environment and form a grid map. It uses the A* algorithm and interpolation method to plan a set of path points within Q meters of the mobile robot's forward route and calculate the corresponding navigation angle.

[0009] S2 uses the laser radar device to determine whether there are obstacles on the forward route, calculates the outline coordinates of the obstacle, and then calculates the outline of the mobile robot and uses the nth path point as the center point of the mobile robot to determine the outline coordinates when the mobile robot reaches the nth path point; and determines whether the obstacle coincides with the mobile robot's path to avoid the obstacle.

[0010] S3 calculates the virtual center point of the obstacle based on the obstacle coordinate information scanned by the laser radar; the virtual center point of the obstacle is the average value of the obstacle coordinates obtained by scanning;

[0011] S4 divides the obstacle scanning coordinates into left and right sides according to the forward route, and calculates the coordinates of the points on the left and right sides that are farthest from the virtual center of the obstacle (x z ,y z ), and select the coordinates of the point closest to the mobile robot (x x ,y x ) as the safe obstacle avoidance point, and then calculate the virtual radius of the obstacle according to the virtual center point of the obstacle through formula (1);

[0012]

[0013] L is the length of the mobile robot, and ΔL is the reserved safety distance;

[0014] S5 replans safety points and generates paths based on the virtual center point and virtual radius of the obstacle; it updates the virtual radius of the obstacle in real time and replans safety points if it increases.

[0015] The above method obtains the original laser point cloud data through a multi-line laser radar device, initializes the grid map, uses the A* algorithm and interpolation method to calculate the set of path points within n meters of the forward route, and calculates the corresponding navigation angle. The contour coordinates of the mobile robot at different points are inferred by the navigation angle. The laser radar device then determines whether there are obstacles in the forward route. If there are obstacles, the coordinates of the obstacle contour points are obtained by the supplementary method, and it is determined whether the obstacle coincides with the forward path of the mobile robot. If so, the coordinates of the virtual center point are determined based on the contour point coordinates, and then the distance from the virtual center point is determined. The coordinates of the nearest and farthest points are obtained, and then the obstacle avoidance area path is determined based on the virtual center as the center of the circle, and the distance between the nearest point and the farthest point, half the length of the mobile robot, and the sum of the reserved distances as the radius, so that the mobile robot can detour according to the obstacle avoidance area path. In this way, the interpolation method can be used to predict in advance whether the obstacle overlaps with the mobile robot, and then the obstacle avoidance path is determined. The obstacle avoidance path passes through half the length of the mobile robot, the distance between the nearest and farthest points, and the sum of the reserved distances, thereby ensuring that obstacles can be avoided more reliably and the accuracy of obstacle avoidance is ensured.

[0016] Furthermore, step S3 includes:

[0017]

[0018] (x k ,y k ) is the virtual center point of the obstacle; (x i ,y i ) is the obstacle coordinate information, i is the i-th position point on the obstacle, and m is the total number of points in the horizontal and vertical directions of the obstacle scan.

[0019] The above settings can obtain the coordinate information of the virtual center point of the obstacle through the obstacle coordinate information.

[0020] Furthermore, step S1 includes: the A* algorithm plans to connect each path point; the evaluation function of the A* algorithm is: f(n)=g(n)+h(n); n is the current path point, f(n) is the evaluation function from the starting point via the path point n to the target point; g(n) represents the actual cost from the starting point to the path point n; h(n) is an estimated value, representing the estimated cost from the path point n to the target point.

[0021] The above settings use the estimated value and actual cost value in the A* algorithm to determine the evaluation function, thereby evaluating whether the path meets the requirements. If it does not meet the requirements, it is determined that the path is uneven, and then interpolation is performed through the interpolation method.

[0022] Furthermore, the interpolation method deletes the uneven path and reinserts new path points, inserting the path point coordinates (xn, yn), and the insertion point coordinate calculation formula is: xn=(x1+x2) / 2; yn=(y1+y2) / 2; (x1, y1) is the nearest path point to the left of the current insertion point, and (x2, y2) is the nearest path point to the right of the current insertion point.

[0023] The above setting obtains new coordinates by taking the middle position of two coordinates, so that coordinates that cannot be directly obtained by lidar scanning can be obtained through supplementary interpolation, ensuring the reliability of the obtained path points.

[0024] Furthermore, through the formula Calculate the navigation angle of different points on the route. The route navigation angle for the nth path planning point.

[0025] The above settings prepare for the subsequent calculation of the mobile robot's navigation angle by calculating the navigation angle of each path planning point.

[0026] Furthermore, the four corner coordinates of the mobile robot calculated according to the navigation angle are:

[0027]

[0028] L is the length of the mobile robot, and W is the width of the mobile robot.

[0029] The above settings calculate the coordinates of the four corners of the mobile robot through the navigation angle, which can more accurately determine whether the outline of the mobile robot overlaps or collides with obstacles at the path points. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is the workflow of the present invention.

[0031] Figure 2 To plan the path point map.

[0032] Figure 3 Calculate the contour map for the mobile robot's forward points.

[0033] Figure 4 To calculate obstacle simulation center points and plan safety point maps.

[0034] Figure 5 It is an obstacle avoidance roadmap based on safe obstacle avoidance point planning. DETAILED DESCRIPTION

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] As Figure 1-5 shown, a mobile robot obstacle automatic avoidance and bypassing method is used for mobile robot obstacle avoidance and path planning, and a laser radar device is arranged on the mobile robot,

[0037] including the following steps:

[0038] S1, the laser radar device acquires surrounding environment information and forms point cloud data, then determines the surrounding environment contour through the point cloud data, initializes the grid map, calculates the path point set within Q meters of the forward route by using A* algorithm and interpolation method, and calculates the corresponding navigation angle.

[0039] The A* algorithm is used to plan and connect each path node; the evaluation function of the A* algorithm is: f(n)=g(n)+h(n); n is the current path point, f(n) is the evaluation function from the starting point to the target point through the path point n; g(n) represents the actual cost from the starting point to the path point n; h(n) is an estimate value, representing the estimated cost from the path point n to the target point;

[0040] The interpolation method deletes the uneven path and inserts new path points, and the insertion point coordinates (xn, yn) are calculated by the formula: xn=(x1+x2) / 2; yn=(y1+y2) / 2; (x1, y1) is the nearest path point on the left side of the current insertion path point, and (x2, y2) is the nearest path point on the right side of the current insertion point.

[0041] The navigation angle of different point positions on the route is calculated by the formula ; and is the route navigation angle of the nth path point position.

[0042] S2, the laser radar device is used to determine whether there is an obstacle on the forward route, calculate the contour coordinates of the obstacle, and then calculate the contour when the mobile robot reaches the n point; the contour four corner coordinates of the mobile robot are calculated according to the navigation angle, which are respectively:

[0043]

[0044] L is the length value of the mobile robot, and W is the width value of the mobile robot.

[0045] The overall contour is calculated in the grid map by using the interpolation method, and it is judged whether the robot collides with the obstacle contour by comparing the robot coordinates with the obstacle coordinate values.

[0046] S3, according to the obstacle coordinate information (x i , y i ) scanned by the laser radar, i is the ith position point on the obstacle, m is the total number of points in the horizontal and vertical directions scanned by the obstacle, and the following formula is used

[0047]

[0048] Calculate the virtual center point of the obstacle;

[0049] S4 divides the obstacle scanning coordinates into left and right sides according to the forward route, and calculates the coordinates of the points on the left and right sides that are farthest from the virtual center of the obstacle (x z ,y z ), and select the coordinates of the point closest to the mobile robot (x x ,y x ) as the safe obstacle avoidance point, and then calculate the virtual radius of the obstacle according to the virtual center point of the obstacle using the following formula:

[0050] safe distance;

[0051] S5 replans safety points and generates paths based on the virtual center point and virtual radius of the obstacle; it updates the virtual radius of the obstacle in real time and replans safety points if it increases.

[0052] like Figure 2-5 As shown, the mobile robot 1 moves on the forward path 2 and there is an obstacle 3 in front. The virtual center point position 30 of the obstacle, as well as the nearest point 32 and the farthest point 33 on the left and right sides of the forward path 2 are determined, and then the safety planning point 31 is determined based on it.

[0053] The working principle of the present invention is as follows: the original laser point cloud data is obtained by the laser radar device, the grid map is initialized, the path point set within n meters of the forward route is calculated using the A* algorithm and the interpolation method, and the corresponding navigation angle is calculated. The contour coordinates of the mobile robot at different points are inferred by the navigation angle, and then the laser radar device is used to determine whether there are obstacles in the forward route. If there are obstacles, the coordinates of the obstacle contour points are obtained by the supplementary method, and it is determined whether the obstacle coincides with the forward path of the mobile robot. If so, the coordinates of the virtual center point are determined according to the contour point coordinates, and then the distance from the virtual center is determined. The coordinates of the nearest and farthest points of the point are calculated, and then the obstacle avoidance area path is determined based on the virtual center as the center of the circle, and the distance between the nearest point and the farthest point, half of the length of the mobile robot, and the sum of the reserved distances as the radius, so that the mobile robot can detour according to the obstacle avoidance area path. In this way, the interpolation method can be used to predict in advance whether the obstacle overlaps with the mobile robot, and then the obstacle avoidance path is determined. The obstacle avoidance path passes through half of the length of the mobile robot, the distance between the nearest and farthest points, and the sum of the reserved distances, thereby ensuring that obstacles can be avoided more reliably and the accuracy of obstacle avoidance is ensured.

Claims

1. A method for automatically avoiding obstacles for a mobile robot, characterized by: The following steps are involved: S1 uses a laser radar device to obtain information about the surrounding environment and form a grid map. It uses the A* algorithm and interpolation method to plan a set of path points within m meters of the mobile robot's forward route and calculate the corresponding navigation angle. S2 uses the laser radar device to determine whether there are obstacles on the forward route, calculates the outline coordinates of the obstacle, and then calculates the outline of the mobile robot and uses the nth path point as the center point of the mobile robot to determine the outline coordinates when the mobile robot reaches the nth path point; and determines whether the obstacle coincides with the mobile robot's path to avoid the obstacle. S3 calculates the virtual center point of the obstacle based on the obstacle coordinate information scanned by the laser radar; the virtual center point of the obstacle is the average value of the obstacle coordinates obtained by scanning; S4 divides the obstacle scanning coordinates into left and right sides according to the forward route, and calculates the coordinates of the points on the left and right sides that are farthest from the virtual center of the obstacle (x z ,y z ), and select the coordinates of the point closest to the mobile robot (x x ,y x ) as the safe obstacle avoidance point, and then calculate the virtual radius of the obstacle according to the virtual center point of the obstacle using the following formula: L is the length of the mobile robot, and ΔL is the reserved safety distance; S5 replans safety points and generates paths based on the virtual center point and virtual radius of the obstacle; it updates the virtual radius of the obstacle in real time and replans safety points if it increases.

2. The method for automatically avoiding obstacles for a mobile robot according to claim 1, characterized in that: Step S3 includes: (x k ,y k ) is the virtual center point of the obstacle; (x i ,y i ) is the obstacle coordinate information, i is the i-th position point on the obstacle, and m is the total number of points in the horizontal and vertical directions of the obstacle scan.

3. The method for automatically avoiding obstacles for a mobile robot according to claim 1, characterized in that: Step S1 includes: the A* algorithm plans to connect each path point; the evaluation function of the A* algorithm is: f(n)=g(n)+h(n); n is the current path point, f(n) is the evaluation function from the starting point to the target point via the path point n; g(n) represents the actual cost from the starting point to the path point n; h(n) is an estimated value, representing the estimated cost from the path point n to the target point.

4. The method for automatically avoiding obstacles for a mobile robot according to claim 1, characterized in that: By formula Calculate the navigation angle of different points on the route. The route navigation angle for the nth path planning point.

5. The method for automatically avoiding obstacles for a mobile robot according to claim 4, characterized in that: The four corner coordinates of the mobile robot's outline are calculated based on the navigation angle: L is the length of the mobile robot, and W is the width of the mobile robot.

Images