An Improved DWA Path Planning Algorithm Integrating Global JPS Strategy

In complex and dynamic environment, current dynamic window approach (DWA) and its improved algorithm are apt to be trapped in local minimum. It is difficult for them to obtain planning path with global optimum. They are also liable to be trapped in a second local minimum. Aiming at these problems, this paper first introduces heuristic functions by building a function of safety level and a function of cardinal direction bias; at the same time, it integrates jump point search (JPS) strategy to obtain path nodes with global optimum, which improves the efficiency of path nodes obtaining and guarantees the safety of the obtained path nodes as well. Then, the obtained path nodes with global optimum are taken as dynamically refreshed goals for DWA. Judging criteria of the second local minimum and replanning framework are set to guarantee the completeness of path planning and the global optimum of the planned path. In the end, simulations of the proposed algorithm are carried out in complex and dynamic environment. The results show that the proposed algorithm effectively solves the problems of local minimum and the second local minimum caused by dynamic obstacles; meanwhile, it also improves the efficiency of path planning and the capability to seek an optimal path.