冗余机械手在危险源环境下的多目标逆解研究  

Study on multi-object inverse-kinematics for redundant manipulators in environment with dangerous source

作　　者：郭西进[1] 高警卫[1] 苑存超[1] 汪秀[1] 

机构地区：[1]中国矿业大学信息与电气工程学院,江苏徐州221008

出　　处：《矿山机械》2012年第5期106-110,共5页Mining & Processing Equipment

基　　金：国家自然科学基金项目(61005089)

摘　　要：针对机械手逆解问题,首次给出了粒子群算法优化机械手的方法,以优化结果确定逆解。其次定义了机械手的危险度概念,并将多目标粒子群算法应用于带有危险源和障碍物环境中的冗余机械手逆运动学研究。相比传统方法,该多目标优化方法不仅确定了冗余机械手的最终形状,而且能够使其成功避障,满足避障可操作、危险度和功率最省或更多的多目标要求。相比多目标遗传算法的仿真结果,该方法可以得到更理想的性能指标,通过进一步的3个指标试验仿真,证明了该方法的正确性和有效性。Contrary to the inverse-kinematics problem of manipulators,an method of optimizing the manipulators with multi-objective particle swarm optimization（MOPSO） was presented for the first time and the results were used to determine the inverse-kinematics.And then the concept of danger degree of manipulators was given and MOPSO was applied to the study of inverse-kinematics of redundant manipulators in working environment with dangerous sources and obstacles.Comparing with traditional methods,the multi-object optimization method could not only determine the final configuration of manipulators,but also make it successfully avoid obstacles and meet the multi-object reqirements such as avoidance manipulability,danger degree and the lowest power.Comparing with the simulation results of multi-objective genetic algorithm（MOGA）,the method could realize better performance.Moreover,the simulation results from three-index test also confirmed the correctness and effectiveness of the method.

关 键 词：冗余机械手 多目标粒子群 逆解 危险度 多目标优化 

分 类 号：TP241.2[自动化与计算机技术—检测技术与自动化装置]