Path Planning for Autonomous Underwater Vehicles Under the Influence of Ocean Currents Based on a Fusion Heuristic Algorithm

Recently, research on path planning for the autonomous underwater vehicles (AUVs) has developed rapidly. Heuristic algorithms have been widely used to plan a path for AUV, but most traditional heuristic algorithms are facing two problems, one is slow convergence speed, the other is premature convergence. To solve the above problems, this paper proposes a new heuristic algorithms fusion, which improves the genetic algorithm with the ant colony optimization algorithm and the simulated annealing algorithm. In addition, to accelerate convergence and expand the search space of the algorithm, some algorithms like trying to cross, path self-smoothing and probability of genetic operation adjust adaptively are proposed. The advantages of the proposed algorithm are reflected through simulated comparative experiments. Besides, this paper proposes an ocean current model and a kinematics model to solve the problem of AUV path planning under the influence of ocean currents.

Automated summary

Research on path planning for AUVs has rapidly progressed, with traditional heuristic algorithms facing issues of slow convergence speed and premature convergence. To address these problems, a new heuristic algorithm combining genetic, ant colony optimization, and simulated annealing algorithms is proposed, alongside additional techniques to accelerate convergence and expand search space. The advantages of the proposed algorithm are demonstrated through simulated comparative experiments, along with the introduction of ocean current and kinematics models for AUV path planning under the influence of ocean currents.