摘要
在移动机器人控制领域,路径规划是最重要并具有挑战性的问题之一。本文首先采用栅格法对环境进行建模,然后提出一种改进的人工蜂群算法用于机器人的路径规划。在该算法中,为了提高人工蜂群算法的收敛速度,提出自适应的搜索方式,并采用精英保留选择策略以避免机器人路径规划陷入局部最优。仿真实验结果表明,所提算法在机器人路径规划上的可行性与有效性。
Path planning problem is one of the most important and challenging issues in mobile robot control field. In this paper,the grid method was used to model the robot working environment firstly. Then an improved artificial colony algorithm was put forward for robot path planning. In this algorithm,an adaptive search method was proposed in order to improve the convergence speed of the artificial colony algorithm and the elitist selection strategy was used to avoid the robot path planning falling into a local optimum. Experimental results show the feasibility and effectiveness of the proposed algorithm in path planning for mobile robots.
出处
《计算机与现代化》
2015年第3期1-4,共4页
Computer and Modernization
基金
国家自然科学基金资助项目(61203365)
江苏省自然科学基金资助项目(BK2012149)
中央高校基本科研业务费专项基金资助项目(2011B04614)
关键词
路径规划
人工蜂群算法
自适应搜索
精英保留选择策略
path planning
artificial colony algorithm
adaptive search
elitist selection strategy
