Research On Robot Path Planning Based On Improved RRT Algorithm

As a popular research field nowadays,mobile robots have been widely used in social life.This paper studies the path planning of mobile robots in complex maps.In view of the differences in the distribution of obstacles in different regions in the real environment map,a Rapidly-exploring Random Tree(RRT)path planning algorithm based on the distribution characteristics of different obstacles is proposed,on this basis,the ant colony system is further integrated to better complete the planning and obtain an efficient and feasible path.The main work of this paper is as follows:First of all,the paper proposes a target bias based on environmental partition RRT algorithm(TEP-RRT).The environmental map is divided into open areas and complex areas according to the number of obstacles in the area.Refer to the target directivity idea of the artificial potential field method,introduce the target bias expansion strategy with weight,and combine it with the adaptive random tree expansion step size.The random probability sampling strategy enables the new node to choose the growth direction of the expansion point according to the environment: In an open area,it grows in the direction of the target point to quickly pass through the area;in a complex area,it grows in the direction of a random point to avoid obstacles and increase the success rate of random tree expansion.Secondly,a TEP-RRT path planning algorithm based on the optimized ant system is proposed.By using the path node information planned by the TEP-RRT algorithm,the distribution of the initial pheromone of the ant colony is improved,and put forward the pheromone accumulation strategy combined with the environmental map,so that the ant colony system converges to the optimal path more efficiently;on this basis,by hopping point screening,redundant nodes in the path are removed,and the path length is optimized.,and the B-spline strategy is used to smooth the path near the obstacle,and the optimal path that meets the requirements of the robot's operation is obtained.Finally,build environment maps of different regional combinations in MATLAB,conduct simulation experiments on the improved TEP-RRT algorithm,and verify the method proposed in this paper based on the ROS experimental platform.Simulation and experimental verification results show that the TEP-RRT algorithm based on the optimized ant system has superiority.