Path Planning Research Of Substation Inspection Robots Based On Multiple Task Points

With the continuous updating and upgrading of the power system,the scale of substations increases and the inspection environment becomes more and more complex.Robotic inspection is quickly replacing manual inspection as a fashion statement.Reasonable path planning is required in order to ensure safe and effective robot inspection.Path planning is an important basis for robot inspection.Therefore,studying the path planning of substation inspection robots is very important.Based on this problem,this paper mainly does the following research:1.The first analysis of substation inspection requirements,including the analysis of substation inspection equipment and substation environment characteristics,summarized the general substation environment has characteristics,followed by the analysis of magnetic navigation,laser navigation,inertial navigation,GPS navigation,visual navigation and other five common positioning technologies,and selected magnetic navigation combined with RFID technology as the navigation and positioning method of the inspection robot in this paper.Finally,the principles and advantages and disadvantages of three typical environmental modeling methods such as visual view method,topology method and grid method are analyzed.According to the characteristics of substation environment,grid method is selected to create a two-dimensional environment model of substation.2.An improved ant colony optimization algorithm is proposed for the substation multi-task point inspection sequencing problem,firstly,To speed up the method’s convergence,the state transfer probability is enhanced using the conventional ant colony technique.Then,the elite ant strategy is introduced and an adaptive adjustment factor is added to improve the pheromone update mechanism,which can dynamically update the global pheromone concentration of the optimal path for each iteration in real time,and prevent the algorithm from falling into local optimality and improve the global search capability of the algorithm.Finally,simulation experiments were carried out with different test examples of city coordinates and the results showed that the improved algorithm performed better.3.Improvements were made to the A~* algorithm to improve the efficiency of the algorithm when performing substation local path planning.Three improvements were made to the A~*algorithm,namely an improved 8-neighbourhood node search strategy,an improved heuristic function,and the screening of optimal turning points in the initial path by an optimal turning point selection strategy.Among them,the improved 8-neighbourhood search strategy can ensure the safety of the inspection robot in the inspection process and reduce the risk of the inspection robot touching an obstacle,the improved heuristic function can promote the productivity and improve the time,and the optimal turning point selection strategy can select the optimal turning point in the generated path,thus reducing the length of the inspection path and reducing the number of turns of the inspection robot.Finally,the final path is fitted by a segmented B spline curve and the effectiveness of the improved A~* algorithm is verified by simulation.4.For substation inspection robots needing to complete multi-task point inspection,a hybrid algorithm consisting of an improved A~* algorithm and an improved ant colony optimization algorithm is used to complete the multi-task point inspection task,and then a segmented B-bar curve is applied to deal with each segment of the path non-smooth problem in turn to produce experimental results.Figure [57] Table [6] Reference [81]...