Path planning based on fuzzy-control dynamic window approach

A method integrating rapidly-exploring random tree (RRT) and improved dynamic window approach (DWA) is proposed to realize obstacle avoidance of mobile robots in complex dynamic obstacle environments. Based on the known environment information, the global optimal safe path is generated using the improved RRT algorithm. To address the problem of too many invalid nodes in the expansion of the RRT algorithm, the efficiency of the algorithm is improved by introducing a bidirectional alternating search (BAS) strategy; the forward search tree and the backward search tree alternate searching paths with new nodes as the target nodes until the paths meet; and the redundant nodes in the paths are removed using path node filtering to shorten the path. Secondly, the DWA algorithm is used to track the improved RRT algorithm to plan the path. When unknown obstacles appear in the environment, the weights of the DWA algorithm evaluation function are dynamically adjusted by fuzzy control to avoid the obstacles and return to the original route in time. Finally, the simulation experiments verify that the proposed improved fusion algorithm in complex dynamic environment has short running time, small path cost, and always keeps a safe distance from the obstacles to ensure the optimal path is tracked while safely avoiding the dynamic obstacles.