A Local Path Planning Algorithm for Robots Based on Improved DWA

In order to solve the problem whereby the original DWA algorithm cannot balance safety and velocity due to fixed parameters in complex environments with many obstacles, an improved dynamic window approach (DWA) of local obstacle avoidance for robots is proposed. Firstly, to assure the path selection stationarity and enhance the navigation ability of inspection robot, the velocity cost function of the original DWA was improved and the distance cost function of the target point was added. Then, the distances among the inspection robot, observed obstacles, and target points were input into a fuzzy control module, and the fuzzy weights of the velocity and distance cost functions were obtained, by which the motion of the inspection robot can continuously self-adjust and adapt to the unknown environment. Finally, several simulations and experiments were conducted. The results show that the improved DWA algorithm can effectively improve the obstacle avoidance ability of inspection robots in complex environments. The path can be more reasonably selected and the safety of inspection robots can be enhanced, while the safe distance, path length, and the number of samples can also be optimized by the improved DWA compared to the original DWA.