The hybrid path planning algorithm based on improved A and artificial potential field for unmanned surface vehicle formations

• Published in: Ocean engineering Vol. 223; p. 108709
• Main Authors: Sang, Hongqiang, You, Yusong, Sun, Xiujun, Zhou, Ying, Liu, Fen
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-03-2021
• Subjects: A global path planning; Multiple sub-target APF local path planning; USV dynamics; USV formation; Multiple sub-target APF local path planning; A global path planning; USV dynamics; USV formation
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2021.108709

To effectively improve system autonomy, increase fault-tolerant resilience, solve low payload capacity and short endurance time of unmanned surface vehicles (USVs), there's a trend to deploy multiple USVs as a formation fleet. The formation path planning algorithms are essential to generate optimal trajectories and provide practical collision avoidance maneuvers to efficiently navigate the USV fleet. To ensure the optimality, rationality and path continuity of the formation trajectories, this paper presents a novel deterministic algorithm named multiple sub-target artificial potential field (MTAPF) based on an improved APF. The MTAPF belongs to the local path planning algorithm, which refers to the global optimal path generated by an improved heuristic A* algorithm. and the optimal path is divided by this algorithm into multiple sub-target points to form sub-target point sequence. The MTAPF can greatly reduce the probability that USVs will fall into the local minimum and help USVs to get out of the local minimum by switching target points. As an underactuated system, the USV is restricted by various motion constraints, and the MTAPF is presented to make the generated path compliant with USV's dynamics and orientation restrictions. The proposed algorithm is validated on simulations and proven to work effectively in different environments.
•Improved A* algorithm is used to obtain optimal marching path, reduce calculation amount and time, guarantee path safety.•Improved APF converts vector force into a potential field. Local path planning ensures real-time performance of formation.•Multiple sub-target APF with improved A* can help USVs escape local minima and ensures optimality and real-time of path.•Hybrid control, leader-follower control and priority strategy are used to avoid USV colliding with each other.