遗传柔性多面体混合算法在机器人时间最优轨迹规划模型的应用  

Application of genetic and flexible polygon hybrid algorithm in the time-optimal trajectory planning of robot

作　　者：陈勇旗[1] 陈启军[1] 谭冠政[2] 

机构地区：[1]同济大学信息与控制系 [2]中南大学,长沙410083

出　　处：《制造业自动化》2007年第3期35-38,共4页Manufacturing Automation

基　　金：教育部博士点基金项目资助(RL200002)

摘　　要：时间最优轨迹规划是机器人技术中一个重要研究领域,本文首先推导出该问题的非线性规划数学模型,在此基础上引入了遗传柔性多面体混合算法,该算法融合了遗传算法的全局搜索能力和柔性多面体算法的局部搜索能力,实验结果表明,遗传柔性多面体混合算法在搜索性能方面超过遗传算法,使机器人在满足约束条件下以更少的时间完成给定轨迹的运行,提高了机器人在制造业中的搬运效率。The time-optimal trajectory planning is an important research in Robotics. In this paper, an nonlinear planning model is deduced firstly. On this basis, the genetic and flexible polygon hybrid algorithm are introduced. This hybrid method integrates the search mechanisms of this two methods and greatly elevates the ability of exploration and exploitation. The experiment shows that this hybrid method is prior to the genetic algorithm in search performance. Through the hybrid method, the robot can accomplish the trajectory in optimal time and the efficiency of robot is improved greatly.

关 键 词：轨迹规划 非线性规划 遗传算法 柔性多面体 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]