Improved A-star Algorithm for Mobile Robot Path Planning Based on Sixteen-direction Search
Wen Bao, Jun Li, Zhihao Pan, Ruixin Yu · 2022
An A-star algorithm is realized by changing the dynamic weights of heuristic functions when path planning in sixteen search directions, improving the problems present in traditional A-star algorithm at some aspects. Firstly, the search direction of the mobile robot is increased and changed from the ordinal eight-direction search to sixteen-direction search against long planning path. Secondly, the dynamic weight adjustment method is given to adjust the weight coefficients of the estimated cost h(n) in the A-star algorithm in real time to address redundant search nodes. Finally, the path is optimized using the turn-angle strategy aim for fewer turning times. Simulation experiments are carried out by MATLAB under a given map and regular maps. The experimental results show that the A-star algorithm studied in this paper has fewer search nodes, higher planning efficiency, shorter path length and fewer turns compared with the traditional A-star algorithm, which verifies the feasibility of the above algorithm.