Research On Path Planning For Hexapod Robot Based On Improved A* Algorithm

Walking robots have better ability to pass through rough roads than wheeled robots,so they have broad application prospects in the field of emergency disaster relief operations.Among them,the hexapod robot has excellent static stability and environmental adaptability,and has obvious advantages in dealing with complex ground,especially the geographical features of mountains and tunnels.However,the hexapod robot can only realize value by moving the corresponding position according to the goal set by the human.Therefore,the path planning technology provides the safety guarantee for the robot to complete the task.At present,the hexapod robot path planning algorithms include ant colony algorithm,artificial potential field method,RRT algorithm,etc.Among them,A*algorithm,as a classic heuristic path planning search algorithm,has the characteristics of convenient use,easy implementation,and ability to quickly find the global optimal path in a static environment.It has been widely used in the path planning of mobile robots.However,the traditional A* algorithm has problems such as round-trip search,poor search efficiency,and redundant points and turning points in the planned path.To address these problems,the main contents of this article are listed as follows:(1)Use grid method and obstacle puffing technology to carry out environmental modeling,analyze the heuristic function and algorithm flow of traditional A* algorithm,and use Matlab software to generate path planning algorithm examples.Analyzing the number of extension points,path planning length,and the execution performance of the algorithm in the algorithm example,it is found that the traditional A* algorithm has problems such as round-trip search phenomenon,many sharp points and inflection points,and long path planning time.(2)By adding the influence of the parent node of the current node to the expansion point in the evaluation function,the number of round-trip searches of the algorithm is reduced,thereby improving the efficiency of the algorithm.Take the key point selection strategy as an indicator to avoid unnecessary turning points and redundant points,and shorten the length of the planned path.Introduce the minimum heap acceleration strategy to speed up path finding.The B-spline function is used to smooth the path with sharp corners and optimize the planned trajectory.Performing multiple sets of simulations in Matlab software,the results show: Compared with the traditional A*algorithm,the path length of the improved A* algorithm is reduced by about 3%,the number of turns is reduced by about 25%,the number of search points is reduced by about 46%,and the running time is reduced.About 17%,and the planned path is smoother.Experiments show that the optimization effect of the improved A* algorithm is better than the traditional A* algorithm in the case of large-size maps and many obstacles.(3)Starting from the hardware and software of the control system,an experimental research platform based on the Raspberry Pi was built to study the path planning of the hexapod robot.In the actual indoor static environment,the improved A*algorithm path planning test is carried out.The test results show that the optimization effect of the improved A*algorithm is almost the same as the simulation effect.Compared with the traditional A*algorithm,the path planning is shorter and smoother.The search time is shorter.This article provides a certain reference for the improvement of the A* algorithm,and has certain significance for the study of hexapod robots and the improvement of path planning efficiency and trajectory rationality.