| Electricity is the pillar of modern economy and society,and with the continuous growth of electricity demand,the need for stable electricity supply becomes more and more obvious.In the development of modernization,intelligent robot inspection has been gradually introduced.This inspection method has the advantages of high efficiency,high accuracy,low cost and high security.It can perform inspection tasks according to the actual situation,but the inspection path needs to be reasonably optimized.The mobile robot can carry out autonomous navigation and path planning,which can meet the basic requirements of inspection,and the premise of device fault detection is to plan a reasonable and smooth collision-free path.In order to make the inspection robot run more smoothly and reduce jitter during the inspection operation,this paper takes the inspection robot of the substation environment as the goal of research.Aiming at the shortcomings of the planned path,it makes improvements based on genetic algorithm,and the detailed research contents are as follows:First,analyze the domestic and foreign research background and current development status of inspection robots and path planning,as well as the basic ideas of optimization algorithms such as genetic algorithm and ant colony algorithm;analyze the defects of the above methods in path planning,and choose the grid method A simplified scene model of the inspection robot in the substation environment is constructed.Secondly,aiming at the redundant points and peak points highlighted in the planning of the genetic algorithm,the genetic algorithm is improved,and the improved adaptive operator and the improved selection operator are added,and the distance,corner,and turn are considered comprehensively for the fitness function.Times and other factors,after the improved genetic algorithm plans out the path,use the B-spline curve to smooth and optimize it.Finally,the inspection robot is simulated using the global static environment of 20*20 and30*30 substations,and the feasibility of the improvement idea is verified by comparing the simulation results.Finally,on the basis of the above theories,the ant colony algorithm is used as the basic planning algorithm for global path planning;for the defects of ACO path search,an improved adaptive smoothing genetic algorithm is introduced,and an improved ant colony fusion improved adaptive genetic algorithm is proposed.The fusion algorithm improves the shortcomings of planning,and finally uses the improved ACO-AGA algorithm for path planning.First use MATLAB to verify the results of the improved fusion algorithm,then use ROS simulation and actual scene planning to verify the feasibility,conduct joint simulation analysis and effect verification of the improved fusion algorithm in Gazebo and rviz,and test the improved fusion algorithm Based on the effect of path planning,it is concluded that the improved fusion ACO-AGA algorithm can complete the inspection task.To sum up,this paper mainly focuses on the path planning of the task points of the inspection robot in the substation environment and the problem of redundant points and peak points in the planning,and improves the algorithm,using the improved fusion adaptive ant colony-genetic The algorithm plans the path for the robot to inspect the equipment.In this method,the improved genetic algorithm is introduced into the improved ant colony algorithm,and the B-spline operator is used for the planned path,and the final running path meets the improved expectations. |
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