Abstract: Optimal path planning for automated operators, such as robots or mechanical arms, in the workspace is of importance to improve the efficiency in terms of minimized operation distance and ensure the operation safety along the optimized working path. The existing path planning algorithms, however, still have some limitations, such as complicated searching process, and most importantly omissions of safety considerations while the searching distance was reduced. An improved A-star optimal path planning algorithm is proposed, which produces safety-insured optimal path that are further fine-tuned with smoothing turning corners. First, a comparison study is carried out for a number of neighborhoods searching algorithms in the family of the A-star approach. It is found that the simplest four neighborhood A-star searching algorithm is often most practical in the searching time, searching distances and the number of turning points. Next, we introduce a matrix in the A-star algorithm, that ensures safety distances for operations along the optimal path. In addition, the heuristic functions used in A-star algorithms are modified to ensure the optimal safety path under different environments. Finally, the optimized path trajectory is further fine-tuned for smoothing corner turnings. The proposed algorithms are tested using a number of examples with complicated obstacles. The results show that our improved A-star algorithm has fewer and smoother turning corners, shorter searching time, and simpler post-processing. Most importantly, it ensures the safety for operations along the optimized path.

Key words: robot, path planning, A-star algorithm, safety distance matrix, heuristic function, path trajectory optimization