To address the limitations of path planning in dynamic environments—namely poor real-time performance and inadequate dynamic obstacle avoidance—a multistrategy-enhanced dynamic window approach is proposed. First, the Anytime Repairing A* (ARA*) algorithm is employed for fast path generation and progressive refinement, producing path nodes aligned with the global objective. Then, within the dynamic window approach (DWA), a velocity adjustment strategy, a multidimensional evaluation function, and adaptive weight parameters are integrated to improve local planning responsiveness and dynamic obstacle avoidance capabilities. Finally, guided by the global path from ARA*, the improved DWA algorithm is used to continuously refine the local trajectory, achieving a coordinated integration of global planning and local avoidance. Simulation results demonstrate that the proposed method significantly enhances both path accuracy and obstacle avoidance performance in dynamic environments.
Meng et al. (Thu,) studied this question.