An Improved JPS Algorithm for Global Path Planning of the Seabed Mining Vehicle

The landscape of the seabed is typical of an unstructured and complicated environment. Long execution time, large memory consumption, and being too close to barriers are all issues in the global path planning of the mining vehicle based on seabed terrain. This study proposes and verifies an improved Jump Point Search (JPS) algorithm to deal with such issues. In terms of calculation speed and memory consumption, the method maintains the advantages of the original JPS algorithm. To begin, the weight of the traversable value is applied to the heuristic function to account for the influence of terrain elements. Second, the method incorporates the improved filtering criteria in a detailed manner. Finally, a suboptimal smoother path is generated by utilizing the Akima algorithm to fit the path. Experimental results reveal that the designed algorithm reduces the execution time of the path and it is more effective than the traditional A* algorithm and generates a safer path than the traditional JPS algorithm.