摘要
针对传统蚁群算法搜索时间长、容易陷入局部最优解等缺点,提出了一种基于组合优化和起始目标导引函数的改进型蚁群算法。为备选结点引入优先级,采用状态转移概率和优先级的组合优化方法平衡各路径信息,避免陷入局部最优。搜索过程引入起始目标导引函数,优先搜索距起点远而距目标点近的结点。仿真结果表明,所提出的改进蚁群算法能够在较短时间内找到全局最优路径,显著提高移动式机器人的路径规划性能。
The problems of traditional ant colony algorithm are searching so long and getting into local solutions easily,we present an improved ant colony algorithm using priority strategy and a start-goal guiding function in searching,In order to get into the local path, we introduced the priority to balance the pheromone of all patbes.In the process of searching,we introduced the start-goal guiding function to search the closest crunode away from the destination.The simulation results show that the improved ant colony algorithm can find the global path within the shortest time,and the algorithm improves the performance of path planning.
出处
《微计算机信息》
北大核心
2008年第20期252-253,212,共3页
Control & Automation
基金
河南省自然科学基金项目(No.0511011700)
关键词
移动机器人
改进蚁群算法
路径规划
mobile robot
improved ant colony algorithm
path planning
