Fangyu Xie∗,∗∗ and Xianpeng Shi∗
Jiaolong manned submersible, optimum quality of path, ant colonyalgorithm, global path planning, path evaluation method
Taking the Jiaolong manned submersible as the research object, this research proposes a global path planning algorithm for a manned submersible based on an improved ant colony algorithm with optimal path quality from several factors, such as driving difficulty, energy consumption and navigation safety. Inspired by the quantitative calculation of “repulsion in the artificial potential field method, we quantified the “density of obstacles around the path point. In the process of selecting path points based on probability, we introduced the perception of the density of obstacles around the path point and the turning of the path, and the paths found by our optimization are far away from obstacles and turn less. Besides, this research quantifies the main factors affecting the path quality and presents an evaluation function of route quality based on multiple perspectives. The function is used to evaluate the quality of the path and its value replaces the path, length as a new basis for updating the pheromone. The simulation results show that the path planned by the improved algorithm in this research has lower driving difficulty, lower energy consumption and higher safety of navigation.
Important Links:
Go Back
