부산대학교 도서관

Biomimetic Autonomous Underwater Vehicles (BAUVs) navigate aquatic environments by mimicking natural propellants from fish species. These vehicles move part(s) of their bodies using various mechanisms to propel and swim forward or laterally. Their main goal is to follow and adjust defined paths to reach a target autonomously. Local path planning is of paramount importance during navigation tasks due to unexpected obstacles. Moreover, path planning strategies should consider the environment’s information obtained by the vehicle during its mission, as well as its dynamics and mechanical limitations, to define new routes properly. This article presents the development of a waypoint generator based on the $\text{D}\ast $ Lite algorithm. The proposed planner considers a frontal-short-sighted and tail-actuated BAUV with motion constraints to adjust the vehicle’s path towards a target coordinate. By identifying obstacles, the planner adjusts and defines inner waypoints inside the vehicle’s vision range by considering closeness to obstacles found and BAUV’s current position. The developed strategy reduces collision risks due to the discrimination of nodes near obstacles, prioritizing broad hallways and safer swimming distances between the vehicle’s current position and inner waypoints. The effectiveness of the proposed algorithm is simulated using the BAUV’s hydrodynamics model and by adding a waypoint tracking controller to correct the vehicle’s swimming performance inside three scenarios. The vehicle can reach the goal by properly defining inner waypoints while safely avoiding collisions, narrow hallways, and sharp turns.