Abstract: An improved ant colony algorithm for global path planning is proposed for the three-dimensional obstacle avoidance optimal path problem of autonomous underwater vehicle under seabed topography. A simple and effective modeling scheme for three-dimensional seabed environment is presented in this paper. In order to improve the insufficiency of the basic ant colony algorithm in practical application, the heuristic function is designed based on global information, and the local and global combination of pheromone updating mode is used to overcome the shortcomings of slow convergence rate and easy to fall into local optimum, which improves the global optimization ability of the algorithm. The length and the smoothness of the path are used as the evaluation function to reduce the path consumption and make the algorithm more practical engineering significance. Simulation results show that the algorithm is effective in large scale seabed environment.

Key words: Autonomous Underwater Vehicle（AUV）, path planning, ant colony algorithm, heuristic function, path consumption

摘要： 针对自主式水下机器人海底地形环境中的三维避障最优路径问题，提出了一种适用于全局路径规划的改进蚁群算法。结合实际情况提出了一种简单有效的三维海底环境建模方案。为了改善基本蚁群算法在实际应用中的不足，根据全局信息设计了启发函数，同时采用局部和全局结合的信息素更新方式，克服算法收敛速度慢、容易陷入局部最优的缺点，提高了算法的全局寻优能力。将路径的长度和路径的光滑度同时作为评价函数，减少路径的消耗，使算法更具备实际工程意义。在大尺度海底环境下仿真验证了该算法的有效性。

关键词: 自主式水下机器人, 路径规划, 蚁群算法, 启发函数, 路径消耗