改进蚁群算法在移动机器人路径规划中的研究

Research of Improved ant Colony Algorithm in Mobile Robot Path Planning

摘要:

移动机器人合理的路径规划是进行探索任务的前提,针对移动机器人路径规划的复杂性,把蚁群算法引入到机器人路径规划中；普通的蚁群算法存在收敛速度慢、效率低和容易陷入局部最优等缺陷,难以直接应用于机器人路径规划中;提出一种在蚁群算法中改进信息素的更新方式、引入最大最小蚁群系统以及改进状态转移规则的移动机器人路径规划方法,在栅格环境下对移动机器人的路径规划进行仿真测试,仿真结果表明该方法能缩小最优路径的查找范围,降低发现最优路径所需的循环次数,能有效提高最优路径的搜索效率,整体性能优于普通蚁群算法。

Abstract:

Reasonable path planning of mobile robot is the premise for exploration missions, in view of the complexity of path planning for mobile robot, the ant colony algorithm is introduced to the robot path planning. The ordinary ant colony algorithm has slow convergence speed, low efficiency and local optimization,is difficult directly applied to the robot path planning, this paper presents an update mode of ants’pheromone,introduction of max min ant system ,and improvement of state transition rules for mobile robot path planning method in ant colony algorithm, the simulation test to mobile robot path planning in grid environment, simulation results shows that this method can reduce the range of searching the optimal path, reduce cycle times of finding the optimal path , improve the efficiency of the optimal path search effectively, the overall performance is better than the conventional ant colony algorithm. 