【摘要】 针对大部分算法在多对角障碍环境中求解最短路径时会穿过对角障碍形成实际不可行路径的问题,提出一种结合对角障碍检测的优化蚁群算法用于移动机器人路径规划.首先采用对角障碍检测标记出条件障碍,然后使用三角选择法准确筛选出可通行和不可通行的条件障碍,最后提出自调整期望启发因子和信息素更新策略.实验结果表明:该算法具有环境适应性强、收敛速度快和寻优能力强的特点,并能有效避免所规划路径穿过对角障碍.更多还原

【Abstract】 For the problem that most of the algorithms will cross the diagonal obstacle to form an actual infeasible path in solving the shortest path in the multi-diagonal obstacle environment, an optimal ant colony algorithm combined with diagonal obstacle detection is proposed for the path planning of mobile robots. First of all, the condition obstacles are marked by diagonal obstacle detection. Then, the trigonometric selection method is adopted to select the passable and impassable condition obstacles accurately. Finally, the self-adjusting expected heuristic factor and pheromone updating strategy are put forward. The experimental result shows that this algorithm has the characteristics of high environmental adaptability, fast convergence speed and strong optimization ability, as well as it can effectively avoid the planned path crossing the diagonal obstacles.更多还原