Communication-constrained coordinated path planning for USV-UAV systems in maritime environments using an improved particle swarm optimization algorithm

Abstract

This paper presents a communication-constrained coordinated path planning method for heterogeneous unmanned surface vehicle (USV)-unmanned aerial vehicle (UAV) systems operating in maritime environments. The path planning problem is formulated as a multi-objective optimization problem that simultaneously considers propulsion energy consumption, obstacle avoidance, communication maintenance, and trajectory smoothness. To enhance the search capability of the conventional Particle Swarm Optimization (PSO), an Improved PSO (IPSO) algorithm is developed by integrating four complementary mechanisms: guided particle initialization, adaptive inertia-weight strategy, Gaussian-based local refinement, and stagnation-triggered Lévy-flight exploration with particle redistribution. These mechanisms improve the balance between global exploration and local exploitation while alleviating premature convergence. Simulation results demonstrate that the proposed IPSO consistently achieves lower optimization cost, shorter coordinated trajectories, and improved solution stability than the conventional Genetic Algorithm (GA) and standard PSO.