Path Planning Of Substation Patrol Robot Based On Improved Ant Colony Fusion Algorithm

Substation is an indispensable part of the power system,and its safety has been closely concerned by experts and scholars at home and abroad.At present,the intelligent level of inspection of substations in China is relatively low,which restricts the development of power grids.For this reason,the national 14 th five-year plan puts forward the goal of accelerating the intelligent transformation of power grid infrastructure and the construction of smart micro-grid.Under the above background,intelligent substation inspection robots have developed rapidly.As one of the key technologies of substation inspection robots,path planning has also been extensively and deeply studied.In order to ensure that the substation inspection robot can plan the shortest path and avoid the detected dynamic obstacles during the inspection process,this paper proposes a hybrid path planning method that combines global path planning and local path planning.The main work is as follows:In this paper,the environmental characteristics of the substation are analyzed first,and on this basis,the grid method is used to construct a digital map,and the complex scene map is simplified into a two-color grid map,which provides basic map data for path planning research.According to the characteristics of substation environment,path planning is divided into global path planning in static environment and local path planning in dynamic environment.In the global path planning of substation static environment,ant colony algorithm is used to plan the global path.Aiming at the slow search efficiency of ant colony algorithm in the substation environment and easy to fall into local optimal solution,the method of cone pheromone initialization,heuristic factor self-adaptation and stimulus-response division of labor is proposed to optimize and improve ant colony algorithm.Then,a cubic B-spline algorithm is used to smooth the global path to improve the path quality.In the local path planning of substation dynamic environment,the dynamic window method is used for local path planning.Aiming at the problem that the substation inspection robot is easy to deviate from the global optimal path,a global orientation angle evaluation factor is proposed to improve the constraint ability of the static global optimal path for the substation inspection robot.Finally,a fusion algorithm is proposed by combining the improved ant colony algorithm and the dynamic window method.This method can realize global optimal path planning in static environment and local obstacle avoidance in dynamic environment,and improve the path planning ability of substation inspection robot.This paper uses MATLAB and PYTHON to build a simulation experiment environment,and conducts simulation experiments on the improved ant colony algorithm,maximum and minimum ant colony algorithm,basic ant colony algorithm,particle swarm algorithm and genetic algorithm proposed in this paper,and conducts practical tests on the ROS platform.The simulation verifies that the improved ant colony algorithm has the advantages of faster convergence speed,smoother path and shorter length than other algorithms in this paper.The improved dynamic window method solves the problem that the substation inspection robot is easy to deviate from the global optimal path,plans the local optimal path,and avoids dynamic obstacles.Experiments in the simulation environment have verified that the fusion algorithm in this paper has strong practicability in the substation environment.