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作 者:刘浩 姜长青[2] LIU Hao;JIANG Changqing(Electromechanic Research Institute,Department of Physics and Electronic Information,Hengshui University,Hengshui 053000,Hebei,China;School of Aeronautics and Astronautics,Tsinghua University,Beijing 100084,China)
机构地区:[1]衡水学院物理与电子信息系机电研究所,河北衡水053000 [2]清华大学航天航空学院,北京100084
出 处:《机械科学与技术》2022年第5期747-754,共8页Mechanical Science and Technology for Aerospace Engineering
基 金:国家自然科学基金项目(51777115)。
摘 要:逆运动学问题是冗余度机器人运动控制、轨迹规划和动力学分析的基础,也是机器人学中最重要的问题之一。针对末端执行器位姿的最小误差为优化目标,建立了适应度函数,将冗余度机械手的逆运动学问题转化为一个等价的优化问题,在种群智能优化算法基础上应用了杂交变异果蝇优化算法(HMFOA)进行冗余度机械手逆运动学问题的求解。采用嗅觉搜索杂交突变机制和视觉搜索的动态实时更新机制,能有效地解决果蝇优化算法(FOA)的收敛问题,并提高算法的收敛速度。为进一步验证HMFOA的有效性,在七自由度机械手上对HMFOA进行了测试,对其结果与FOA、LGMS-FOA和AE-LGMS-FOA等算法进行了比较,实验结果表明HMFOA能有效地解决冗余机械手的逆运动学问题。Inverse kinematics is the basis of motion control,trajectory planning and dynamics analysis of redundant robots,and it is also one of the most important problems in robotics.Aiming at the minimum error of the position and pose of the end effecter as the optimization objective,the fitness function is established,and the inverse kinematics problem of redundant manipulator is transformed into an equivalent optimization problem.Based on the swarm intelligence optimization algorithm,the hybrid mutation fruit fly optimization algorithm(HMFOA)is applied to solve the inverse kinematics problem of redundant manipulator.Using olfactory search hybrid mutation mechanism and visual search dynamic real-time update mechanism can effectively solve the convergence problem of fruit fly optimization algorithm(FOA)and improve the convergence speed of the algorithm.In order to further verify the effectiveness of HMFOA,HMFOA is tested on a 7-DOF manipulator,and the results are compared with FOA,LGMS-FOA and AE-LGMS-FOA.The experimental results show that HMFOA can effectively solve the inverse kinematics problem of redundant manipulators.
分 类 号:TH16[机械工程—机械制造及自动化]
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