Research On Path Planning Of Intelligent Inspection Robot In Substation

With the development of power systems,the scale of substations is getting larger and larger,and the operating environment is becoming more and more complex.Because of its intelligence and safety,inspection robots will replace manual inspections as an inevitable trend for future development.At present,many research achievements have been made on the application of inspection robots in substations at home and abroad,but how to quickly and accurately plan the efficient and safe operation path of robots is the focus and difficulty of completing inspection tasks.Aiming at this problem,this paper conducts in-depth research on the path planning of inspection robots in substations from three aspects: substation environment modeling,global path planning based on improved ant colony algorithm,and local path planning based on improved artificial potential field method.There are two basic requirements for the path planning of inspection robots: one is that one point can accurately reach another point in the actual environment;the other is that no obstacles will be encountered during operation.In this paper,based on the research on the needs of substation inspection,the 220 k V substation environment is simplified and abstracted.The grid map is used to model the actual environment and the inspection task points are marked.Choose the ant colony algorithm to plan the global path,analyze and study the ant colony algorithm,and discuss the influence of the parameters on the results.Analysis and simulation show that the ant colony algorithm has a long optimization time and may not necessarily obtain the optimal solution.Shortcomings.Aiming at the shortage of ant colony algorithm,the ant colony algorithm is improved from two aspects: optimization of expectation function and optimization based on bacterial foraging method.The simulation is based on the substation map model.The simulation results show that the improved ant colony algorithm has significantly faster convergence speed than the traditional ant colony algorithm,and can find the global optimal solution faster and the shorter distance.In view of the situation that the inspection robot encounters unknown obstacles,on the basis of the global path planning results,the local path planning based on theartificial potential field algorithm is selected,and by changing the relative distance between the target point and the robot and the unknown obstacle and the robot The relative motion speed improves the algorithm.The simulation results show that the improved artificial potential field algorithm solves the shortcomings of the traditional artificial potential field algorithm that may fall into the local minimum and fail to reach the target point,and can quickly and smoothly avoid dynamic obstacles.This paper combines global path planning and local path planning to jointly complete the inspection task of the robot in the substation,where the local is performed on a global basis,but the two search processes are independent of each other.This hybrid algorithm can effectively solve the robot in the substation Path planning problems in complex environments with unknown obstacles.