Work

Multi-USV cooperative path planning via FSM-based distance field and enhanced hippopotamus optimization

Year: 2025

Type: article

Abstract: With single Unmanned Surface Vehicle (USV) no longer meeting growing mission demands, cooperative multi-USV systems have become essential, particularly in obstacle-rich waters where task allocation deviates and path planning struggles to balance distance and safety. To address these challenges, an integrated framework combining a constrained-distance-based Hungarian assignment algorithm and an improved Hippopotamus Optimization algorithm (CDH-IHO) is developed to achieve simultaneous target assignment and path planning (STAPP). The CDH module achieves globally optimal assignment by exploiting a constrained distance matrix constructed through the Fast Sweeping Method (FSM), while the IHO module introduces a Cubic chaotic map and a mutation operator to enhance convergence and avoid local optima. Distance, turning angle, safety, and penalty terms are jointly considered for collision-free path generation. Simulations in five scenarios verify global optimality in assignment and superior performance in path length, smoothness, and safety. CDH-IHO provides an efficient and robust solution for STAPP.

Source: International Journal of Naval Architecture and Ocean Engineering

DOI: 10.1016/j.ijnaoe.2025.100714

Authors: Youjia Han, Huibin Wang

Institution: Hohai University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funders: National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, Fundamental Research Funds for the Central Universities