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This paper proposes an unmanned aerial vehicles (UAVs)-unmanned surface vehicle (USV) collaborative coverage path planning method for island-reef waters using an improved ant colony optimization (ACO) algorithm. The approach first transforms the coverage problem into a multi-travelling salesman problem (M-TSP) by partitioning the monitoring area and designing a task allocation strategy. To ensure full coverage and minimize task completion time, the improved ACO algorithm solves the TSP for the UAVs and USV respectively, with enhancements including adjusted initial pheromone concentration, elite strategy, local path optimization, and an obstacle repulsion term in the heuristic function. Simulation results show the improved ACO significantly boosts convergence speed and path quality compared to the traditional algorithm, demonstrating applicability to monitoring waters with varying scales and island-reef distributions.

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UAVs-USV Collaborative Coverage Path Planning for Island and Reef Waters Based on Improved ACO Algorithm

  • 会议论文

  • 发表日期：

    2026年

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  • Long Tang,
  • Bing Wang,
  • Yu Wang,
  • Yuquan Chen

摘要

This paper proposes an unmanned aerial vehicles (UAVs)-unmanned surface vehicle (USV) collaborative coverage path planning method for island-reef waters using an improved ant colony optimization (ACO) algorithm. The approach first transforms the coverage problem into a multi-travelling salesman problem (M-TSP) by partitioning the monitoring area and designing a task allocation strategy. To ensure full coverage and minimize task completion time, the improved ACO algorithm solves the TSP for the UAVs and USV respectively, with enhancements including adjusted initial pheromone concentration, elite strategy, local path optimization, and an obstacle repulsion term in the heuristic function. Simulation results show the improved ACO significantly boosts convergence speed and path quality compared to the traditional algorithm, demonstrating applicability to monitoring waters with varying scales and island-reef distributions.