A Study on the Optimized Solution of Redundant Manipulators Using Improved General-Weighted Least-Norm Method

Jie Qiu, Kun Xu, Wenqian Hu, Ziwu Ren
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Abstract

This paper presents the improved general-weighted least-norm (IGWLN) method to heighten the optimization ability for the control of redundant manipulator. The IGWLN method ameliorates the mapping relationship between the optimization target and virtual joint by modifying the transformation matrix, which guarantees the accuracy of main task while accomplishing the subtask and reduces the computation compared with the original general-weighted least-norm (GWLN) method. A simulation in contrast to the GWLN method on a seven-degree-of-freedom (7 DOF) redundant manipulator demonstrates the advantages of the IGWLN method while following a given trajectory.
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基于改进广义加权最小范数方法的冗余机械臂优化解研究
提出了一种改进的广义加权最小范数(IGWLN)方法,以提高冗余度机械手控制的优化能力。该方法通过修改变换矩阵来改善优化目标与虚拟关节之间的映射关系,在保证主任务精度的同时完成子任务,与原广义加权最小范数(GWLN)方法相比减少了计算量。通过对7自由度冗余机械臂的仿真对比,验证了该方法在给定轨迹下的优越性。
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