基于滑移预测的月球车路径规划研究

LUNAR ROVER PATH PLANNING BASED ON SLIP PREDICTION

月球车是探测月球的多功能机器人,搭载人类对月球的探测任务,主要包括月表环境探测、样本数据搜集以及数据分析等任务。月表地形的复杂度加大了路径规划的难度,地形坡度、撞击坑以及各种障碍物的地形因素不同,使月球车路径规划易陷入危险地形、偏离预计目标和侧翻等状况。因此合理的滑移预测能有效减少路径规划的危险性,缩短路径搜索的时间,优化最优路径长度。针对月球车路径规划算法普遍存在易陷入局部最优解、易陷入危险环境、忽略环境建模技术与路径规划算法的相互适用性等问题,提出一种基于虚拟三维月表环境的改进遗传算法。通过设置遗传因子不变,加入地形综合代价函数设置适应度函数。经过仿真实验,验证了该算法的搜索性能,其收敛速度快、稳定性高。

Lunar rover is a multi-functional robot for exploring the moon.It performs human lunar exploration missions,including environmental exploration of the lunar surface,sample data collection and data analysis.The complexity of the lunar terrain increases the difficulty of path planning.Due to the terrain slope,impact crater and terrain factors of various obstacles,the path planning of lunar vehicle is easy to fall into dangerous terrain and deviate from the expected target and rollover.Therefore,reasonable slip prediction can effectively reduce the risk of path planning,shorten the path search time,and optimize the path length.The lunar rover path planning algorithm is easy to fall into local optimal solution and dangerous environment,ignoring the mutual applicability of environmental modeling technology and path planning algorithm.To solve this problem,we propose an improved genetic algorithm based on the virtual three-dimensional lunar surface environment.By setting the genetic factor unchanged,the terrain comprehensive cost function was added to set the fitness function.The simulation results show that the improved genetic algorithm has the advantages of good search performance,fast convergence and high stability.