Robot Path Planning Integrating the Improved JPS Algorithm and the DWA Algorithm

To address the issues of excessive node expansion and lengthy path planning in the traditional A algorithm, as well as the problems of numerous invalid jump points and unsafe trajectories in the conventional Jump Point Search (JPS) algorithm, this research proposes an enhanced Quadratic Jump Point Search (QJPS) algorithm. The algorithm introduced in this paper employs pruning techniques to eliminate redundant nodes, optimizes the evaluation function to enhance path planning efficiency, and applies obstacle inflation to ensure path safety. Additionally, the improved Dynamic Window Approach (DWA) is integrated to enable smoother path planning and intelligent obstacle avoidance. Experimental results show the proposed QJPS algorithm significantly outperforms traditional ones.