Autonomous Navigation of Robots Based on the Improved Informed-RRT∗ Algorithm and DWA

Abstract

An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS) platform. The simulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%, and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively.