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Path planning method for inspection robot based on map grid and potential field method for obstacle avoidance

An inspection robot and path planning technology, which is applied in the direction of instruments, two-dimensional position/channel control, vehicle position/route/height control, etc., can solve the problems of prolonged robot inspection time and low path planning efficiency, and improve Complete efficiency, improve effectiveness, and shorten path distance

Active Publication Date: 2019-12-13
ELECTRIC POWER SCI RES INST OF GUIZHOU POWER GRID CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a path planning method for inspection robots that combines map grid and potential field method to avoid obstacles, so as to solve the problem that the path planning efficiency of robot inspection path planning in the prior art is not high, resulting in Technical issues such as extension of robot inspection time

Method used

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  • Path planning method for inspection robot based on map grid and potential field method for obstacle avoidance
  • Path planning method for inspection robot based on map grid and potential field method for obstacle avoidance
  • Path planning method for inspection robot based on map grid and potential field method for obstacle avoidance

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Embodiment 1

[0068] combine figure 1 , figure 1 It is the overall flow chart of the present invention. First, global path planning is carried out, and a global optimal path from the starting point to the target point is obtained by using the grid method; according to this optimal path, it moves to the target point, and judges whether it encounters an obstacle. If not, it continues to move to the target point. Otherwise, carry out local obstacle avoidance path planning; for local obstacle avoidance path planning, use the artificial potential field method with variable parameters for obstacle avoidance path planning, and judge whether to reach the target point, if not, continue to move to the target point, otherwise end.

Embodiment 2

[0070] combine figure 2 , figure 2 This is the flow chart of the global path planning program of the present invention. First, grid the site to determine the target point, obstacles and the grid where the robot itself is located; initialize the grid, mark the grid with obstacles as 1, and mark the free grid as 0; search for the adjacent grids of the robot, select From the free grid, define the evaluation function h(Grid[i,j]) to calculate the distance between the center point of this grid and the center point of the target grid: Grid[i,j] is the coordinates of the grid adjacent to the grid where the robot is located, and goal represents the grid coordinates of the target point; compare the h(Grid[i,j]) values ​​of each grid, and select the [i,j]) the smallest grid Grid[i,j] min , set Grid[i,j] min The grid is used as the grid that the robot will move to next; it is judged whether the robot has reached the target point, if not, it will continue to search the adjacent gri...

Embodiment 3

[0072] combine image 3 , image 3 This is the flow chart of the local obstacle avoidance path planning procedure of the present invention. First initialize the parameters of the potential field function, d1: the distance between the robot's current position and the obstacle observed by the lidar, k1: the repulsion weighting coefficient, which is temporarily set to 0.5, and is adjusted according to the obstacle avoidance effect during the debugging process. d2: The distance between the robot's current position and the target position point, k2: The gravity weighting coefficient, temporarily set to 0.5, and the specific adjustment is made according to the obstacle avoidance effect during the debugging process; then the global lidar sensor is used to judge the encountered obstacles Whether to move, if not, calculate the repulsive force and gravitational force directly according to the initialized parameters; otherwise, obtain the motion vector of the obstacle and the relative p...

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Abstract

The invention discloses an inspection robot path planning method combining map grids with potential field method obstacle avoidance; the inspection robot path planning method comprises the following steps: 1, global grid method path planning: using the grid method to obtain the global optimal path from a start point to an object point; 2, moving to the object point: determining whether obstacles are encountered or not, moving to the object point is no obstacle is detected, planning a local obstacle avoidance path if an obstacle is detected until reaching the object point; 3, planning the local obstacle avoidance path, using the artificial potential field method with changeable parameters to carry out obstacle avoidance path planning, determining whether the object point is reached or not, returning to step 2 if not, and finishing the tour if the object point is reached. The inspection robot path planning method can solve the problems that the robot inspection path planning in the prior art is poor in efficiency, thus enlarging the robot inspection time.

Description

technical field [0001] The invention belongs to the technical field of obstacle avoidance path planning for an inspection robot, and in particular relates to a path planning method for an inspection robot combining a map grid and a potential field method for obstacle avoidance. Background technique [0002] Inspection robot is a kind of mobile robot. It is an important inspection equipment in the modern substation system. It is mainly used to monitor various instruments and meters in the substation instead of humans. The obstacle avoidance of the inspection robot is a crucial part of the robot path planning, and the different distribution of obstacles in the environment directly affects the planned path. The choice of obstacle avoidance algorithm is directly related to the effect of path planning. [0003] In practice, the robot's environment is neither completely known nor completely unknown in most cases, but partly known and partly unknown. In view of this situation, th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02
CPCG05D1/0214G05D1/0223G05D1/024G05D1/0257
Inventor 高吉普徐长宝罗显跃杨华龙征张历辛明勇王宇刘斌鲁彩江肖林林呈辉戴宇
Owner ELECTRIC POWER SCI RES INST OF GUIZHOU POWER GRID CO LTD
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