摘要
在现代化自动仓储系统复杂的环境中,障碍物的分布情况是不确定的。为了更好地解决自动导引车(AGV)的避障问题,在人工势场法的基础上,提出了一种基于混沌优化改进的人工势场法。该方法可以有效地解决传统人工势场法存在的目标不可达、局部极小值等问题,使自动导引车能成功规划出一条平滑无碰撞的最优路径。Matlab仿真实验结果表明了该方法的有效性。
In the complex environment of modern automatic storage system,the distribution of obstacles is uncertain.In order to solve the problem of obstacle avoidance of automatic guided vehicle(AGV),on the basis of artificial potential field method,an improved artificial potential field method based on chaotic optimization is proposed.The method can effectively solve the problems of existing goal unreachable and local minimum value of the traditional artificial potential field method,making the automated guided vehicle successfully plan a smooth and collision free collision free optimal path.The Matlab simulation results show the effectiveness of the method.
作者
吴渊博
李兴广
陈殿仁
赵宾锋
徐晨
Wu Yuanbo;Li Xingguang;Chen Dianren;Zhao Binfeng;Xu Chen(School of Electronic & Information Engineering, Changchun University of Science and Technology, Changchun 130022, China)
出处
《科技创新导报》
2017年第17期150-153,共4页
Science and Technology Innovation Herald
基金
吉林省科技发展规划项目(项目编号:20150204033GX)
关键词
混沌优化
人工势场法
自动导引车
避障
Chaotic optimization
Artificial potential field method
Automatic guided vehicle
Obstacle avoidance
