摘要
描述了一种静态环境下机器人路径规划的改进蚁群算法.该算法使用栅格法对机器人的工作空间进行建模.通过模拟蚂蚁的觅食行为,使蚂蚁在起始点和目标点之间采用折返的方式完成最优路径的搜索,增强了蚂蚁搜索的多样性;搜索过程采用"惯性原则"和最大信息素搜索策略,使蚂蚁对最优路径更为敏感;同时,根据信息素在栅格模型中散播的特点,提出一种新的信息素更新策略和散播方式,加快解的收敛速度.仿真结果验证了该算法的有效性,即使在障碍物复杂的地理环境,用本算法也能迅速规划出最优路径.
An improved ant colony algorithm is proposed for robot path planning under a static environment. Grid method is used to establish workspace model of the robot. By simulating the foraging behavior of ant colony, search for optimal path is completed with the way of fold-back iterating between the start and target point for ants, and diversity of the search is enhanced. ＂Inertia principle＂ and the strategy of the most pheromone search are used to make ants more sensitive to the optimal path during the searching process. Meanwhile, according to the features of the pheromone strewing in the grids, a new strewing method and updating strategy of pheromone is reconstructed to accelerate convergence of the solution. Validity of the proposed algorithm, with which optimal path can be planned rapidly even in the geographic conditions with obstacles exceedingly complicated, is demonstrated by the simulation results.
出处
《机器人》
EI
CSCD
北大核心
2008年第6期554-560,共7页
Robot
基金
国家科技支撑计划资助项目(2007BAQ0003403)
宁夏自然科学基金资助项目(NZ0697)
宁夏高等学校科学技术研究项目(2006JY018)
北方民族大学科学研究项目(2004Y022)
关键词
栅格法
路径规划
蚁群算法
机器人
gird method
path planning
ant colony algorithm
robot
