Optimum Selection of Mechanism Type for Heavy Manipulators Based on Particle Swarm Optimization Method  

作　　者：ZHAO Yong CHEN Genliang WANG Hao LIN Zhongqin 

机构地区：[1]State Key Laboratory of Mechanical System and Vibration,Shanghai Jiao Tong University [2]Shanghai Key Laboratory of Thin-wall Structure Manufacturing Technology,Shanghai Jiao Tong University

出　　处：《Chinese Journal of Mechanical Engineering》2013年第4期763-770,共8页中国机械工程学报（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant No. 51075259);Program for New Century Excellent Talents in University of Ministry of Education, China (Grant No. NCET-10-0579);National Basic Research Program of China (973 program, Grant No.2006CB705407);Key Technologies R&D Program of Shanghai,China (Grant No. 10111100203)

摘　　要：The mechanism type plays a decisive role in the mechanical performance of robotic manipulators. Feasible mechanism types can be obtained by applying appropriate type synthesis theory, but there is still a lack of effective and efficient methods for the optimum selection among different types of mechanism candidates. This paper presents a new strategy for the purpose of optimum mechanism type selection based on the modified particle swarm optimization method. The concept of sub-swarm is introduced to represent the different mechanisms generated by the type synthesis, and a competitive mechanism is employed between the sub-swarms to reassign their population size according to the relative performances of the mechanism candidates to implement the optimization. Combining with a modular modeling approach for fast calculation of the performance index of the potential candidates, the proposed method is applied to determine the optimum mechanism type among the potential candidates for the desired manipulator. The effectiveness and efficiency of the proposed method is demonstrated through a case study on the optimum selection of mechanism type of a heavy manipulator where six feasible candidates are considered with force capability as the specific performance index. The optimization result shows that the fitness of the optimum mechanism type for the considered heavy manipulator can be up to 0.578 5. This research provides the instruction in optimum selection of mechanism types for robotic manipulators.The mechanism type plays a decisive role in the mechanical performance of robotic manipulators. Feasible mechanism types can be obtained by applying appropriate type synthesis theory, but there is still a lack of effective and efficient methods for the optimum selection among different types of mechanism candidates. This paper presents a new strategy for the purpose of optimum mechanism type selection based on the modified particle swarm optimization method. The concept of sub-swarm is introduced to represent the different mechanisms generated by the type synthesis, and a competitive mechanism is employed between the sub-swarms to reassign their population size according to the relative performances of the mechanism candidates to implement the optimization. Combining with a modular modeling approach for fast calculation of the performance index of the potential candidates, the proposed method is applied to determine the optimum mechanism type among the potential candidates for the desired manipulator. The effectiveness and efficiency of the proposed method is demonstrated through a case study on the optimum selection of mechanism type of a heavy manipulator where six feasible candidates are considered with force capability as the specific performance index. The optimization result shows that the fitness of the optimum mechanism type for the considered heavy manipulator can be up to 0.578 5. This research provides the instruction in optimum selection of mechanism types for robotic manipulators.

关 键 词：robot manipulators performance analysis type selection particle swarm optimization 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]