AI & ML
Joint-Angle Invariance of Jacobian-Based Performance Indices for Serial Robotic Manipulators
arXiv cs.RO0 views
arXiv:2610.29570v1 Announce Type: new Abstract: This article investigates the joint-angle invariance (JAI) of Jacobian-based performance indices for serial robotic manipulators. We identify kinematic conditions under which representative performance indices, including manipulability, stiffness, and other Jacobian-derived indices, remain independent of the first and last joint angles. This property allows a systematic reduction in the effective configuration-space dimensionality, thereby simplifying the performance evaluation. The utility of JAI is demonstrated through two application scenarios: workspace performance map construction and task layout optimization. Comparative results show that the proposed JAI-based strategy reduces computational effort and storage requirements without compromising the effectiveness.
Source:https://arxiv.org/abs/2610.29570PreviousMixture of Flow Matching and Particle Filter for Proprioception-Based Online Contact EstimationNextEnd-to-End Reinforcement Learning for Quadrupedal Jumping in Lunar Gravity
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