基于蚁群算法的深海着陆车路径规划

doi:10.12382/bgxb.2021.0342

摘要/Abstract

摘要： 针对深海着陆车海底作业“路径最优”问题，提出一种适用于着陆车的三维海底全局路径规划算法。采用栅格等分法建立着陆车作业区域的三维海底环境抽象模型。通过对着陆车航行过程动力学分析和驱动电机速度与工作效率测试，建立其航行运动能耗模型。采用局部和全局信息素更新的基于蚁群寻优的能耗-距离路径规划算法，并将能耗、距离引入到启发函数与评价函数中。仿真实验结果表明，该算法通过合理选取评价函数权重参数，能有效均衡路径规划的里程与能耗，具有较好的收敛速度和全局搜索能力，能够满足深海着陆车海底科考作业需求。

关键词: 深海着陆车, 能耗, 路径规划, 蚁群算法

Abstract: A three-dimensional subsea global path planning algorithm suitable for landing vehicles is proposed for “path optimization” of undersea operation of，deep-sea landing vehicles. The grid equal division method is used to establish a 3D submarine environment abstract model for the operating area of landing vehicle. An energy consumption model of navigation movment of landing vehicle is established by dynamically analyzing the navigation process of landing vehicle and testing the speed and work efficiency of driving motor. Local and global pheromone update-based energy consumption-distance path planning algorithm based on ant colony optimization is adopted，and the energy consumption and distance are introduced into heuristic and evaluation functions. The experimental results show that the proposed algorithm can effectively balance the mileage and energy consumption of path planning by reasonably selecting the weight parameters of the evaluation function. It has good convergence speed and global search ability，and can meet the needs of subsea scientific research operation of deep-sea landing vehicle.

Key words: deep-sealandingvehicle, energyconsumption, pathplanning, antcolonyalgorithm

中图分类号:

TP273

郭威，吴凯，周悦，孙洪鸣，徐高飞，高森. 基于蚁群算法的深海着陆车路径规划[J]. 兵工学报, 2022, 43(6): 1387-1394.

GUO Wei， WU Kai， ZHOU Yue， SUN Hongming， XU Gaofei， GAO Sen. Path Planning of Deep-sea Landing Vehicle Based on Ant Colony Algorithm[J]. Acta Armamentarii, 2022, 43(6): 1387-1394.

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