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作 者:沈孝龙 王吉芳[1] Shen Xiaolong;Wang Jifang(Mechanical Electrical Engineering School,Beijing Information Science&Technology University,Beijing 100192,China)
机构地区:[1]北京信息科技大学机电工程学院,北京100192
出 处:《机械传动》2022年第7期24-30,共7页Journal of Mechanical Transmission
基 金:北京信息科技大学促进高校内涵发展重点培育项目(5212010925)。
摘 要:为简化机械臂逆运动学求解方法与提高解的精度,增强方法的普适性,利用智能优化算法,将运动学逆解变为最优化问题。首先,根据正运动学方程建立末端位姿误差目标函数,结合最佳柔顺性与能耗约束构建适应度函数,使机械臂在满足位姿误差要求时还具有最佳柔顺性与较低能量消耗;为使位置和姿态收敛精度统一并控制进化方向,引入位姿平衡系数与位姿误差调节系数;其次,把个体寻优出色的天牛须搜索与群体优化性能出色的差分进化算法融合,以此提高算法的收敛精度与速度;最后,对6R机械臂与冗余机械臂进行了逆解实验。结果表明,所提算法收敛精度高、速度快、通用性好。In order to simplify the solution method of inverse kinematics of the manipulator,improve the accuracy of the solution,and enhance the universality of the method,the intelligent optimization algorithms are used to turn the inverse kinematic solution into an optimization problem.Firstly,the objective function of the end pose error according to the positive kinematic equation is established,and the best flexibility and energy consumption constraints to construct the fitness function are combined so that the manipulator has the best flexi⁃bility and lower energy consumption when meeting the requirements of the pose error;In order to unify the accu⁃racy of position and attitude convergence and control the evolution direction,the pose balance coefficient and the pose error adjustment coefficient are introduced;Then,the individual optimization of the beetle search with excellent performance in group optimization is integrated with the differential evolution algorithm,so as to im⁃prove the convergence accuracy and speed of the algorithm;Finally,inverse solution experiments are conduct⁃ed on the 6R manipulator and the redundant manipulator.The results show that the proposed algorithm has high convergence accuracy,a fast speed and a good versatility.
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