Multi-objective Performance Optimization of Robotic Mechanism
Based on the kinematics of an industrial robot,the three indices,including global kinematic average value,global kinematic volatility value,global kinematic worst value are analyzed and optimized by multi-objective optimization algorithm.The link length parameters of robot are design as the variable,and the multi-objective optimization model is established by the requirements of the robot workspace and kinematics.An improved multi-objective particle swarm optimization (pso) algorithm is proposed by using the distribution entropy and its difference of an approximate Pareto front to assess the diversity and evolutionary status of the population,and getting feedback information to design evolution strategy.Finally,a group of optimum link length is calculated by using this method.The optimized link length parameters of robot can improve the performance index of the robot greatly.
robot kinematics performance index Pareto entropy multi-objective particle swarm optimization
Mingfeng Ying Xiaohui Mo Jin Jiang
Jinling Institute of Technology Nanjing,China
国际会议
重庆
英文
459-463
2016-03-20（万方平台首次上网日期，不代表论文的发表时间）