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Aiming at the complex seafloor environment,a 3-D path planning method for autonomous underwater vehicle based on the improved ant colony optimization(ACO)algorithm is proposed in this paper.Firstly it introduces the three-dimensional(3-D)spatial modeling method and the standard ACO algorithm,then by taking advantage of excellent characteristics of the ACO algorithm such as distributed computation mechanism,relatively strong robustness and information positive feedback,and improving the pheromone updating strategy and the heuristic function,a 3-D path planning method for autonomous underwater vehicle based on the improved ACO algorithm is proposed.Finally,several path planning experiments are tested on a 30km×30km seafloor region.The experimental results show that the proposed method in the paper can effectively overcome some defects of the standard ACO algorithm such as slow search speed and slow convergence speed,greatly improve the feasibility and effectiveness of path planning and realize the underwater vehicle path planning under the complex seafloor environment well.
Aiming at the complex seafloor environment, a 3-D path planning method for autonomous underwater vehicle based on the improved ant colony optimization (ACO) algorithm is proposed in this paper. First introduced it in the three-dimensional (3-D) spatial modeling method and the standard ACO algorithm, then by taking advantage of excellent characteristics of the ACO algorithm such as distributed computation mechanism, relatively strong robustness and information positive feedback, and improving the pheromone updating strategy and the heuristic function, a 3-D path planning method for Several experiments were carried out on a 30km × 30km seafloor region. The experimental results show that the proposed method in the paper can capable overcome some defects of the standard ACO algorithm such as slow search speed and slow convergence speed, greatly improve the feasibility and effectiveness of path planning and realize the underwater vehicle path planning under the complex seafloor environment well.