Multi-objective path planning for unmanned surface vehicle with currents effects

• Published in: ISA transactions Vol. 75; pp. 137 - 156
• Main Authors: Ma, Yong, Hu, Mengqi, Yan, Xinping
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.04.2018
• Subjects: Currents; Dynamic augmented multi-objective particle swarm optimization; Multi-objective path planning; Unmanned surface vehicle; Unmanned surface vehicle; Multi-objective path planning; Currents; Dynamic augmented multi-objective particle swarm optimization
• ISSN: 0019-0578; 1879-2022; 1879-2022
• DOI: 10.1016/j.isatra.2018.02.003

This paper investigates the path planning problem for unmanned surface vehicle (USV), wherein the goal is to find the shortest, smoothest, most economical and safest path in the presence of obstacles and currents, which is subject to the collision avoidance, motion boundaries and velocity constraints. We formulate this problem as a multi-objective nonlinear optimization problem with generous constraints. Then, we propose the dynamic augmented multi-objective particle swarm optimization algorithm to achieve the solution. With our approach, USV can select the ideal path from the Pareto optimal paths set. Numerical simulations verify the effectiveness of our formulated model and proposed algorithm. •A multi-objective nonlinear optimization model with current effects is formulated.•Dynamic augment MOPSO is designed to resolve a multi-objective path planning problem.•Unmanned surface vehicle can select the preferred path from the optimal paths set.•The model fits well with varied environment boundaries and different current models.