Efficient obstacle avoidance and path planning for mobile agent through complicated environments

Abstract

The Dynamic Window Approach (DWA) suffers from unreasonable planning or is prone to obstacle avoidance failure when the mobile agent operates in a complex environment with dense obstacle distribution. An improved DWA path planning algorithm (IDWA) is proposed to address the above problems. Firstly, the heading angle function is modified to improve navigation ability for mobile agent reaching at the target point while ensuring operational safety. Secondly, the obstacle function is optimized to avoid the agent going around the obstacle's edge. Finally, a complex scenario with multiple obstacles of different passing difficulties is constructed to verify the feasibility of the proposed method. Simulation experiments show that IDWA significantly improves the agent's passage efficiency and local search ability, and the path planning is more reasonable with smaller path deviation and heading deviation.