Event
Study on Joint-Angle Invariance of Jacobian-Based Metrics for Serial Manipulators Accepted to IROS 2026
1 reports · 1 sources
Yaohua Zhou and other researchers proposed and validated the joint-angle invariance (JAI) condition for Jacobian-based performance metrics (such as manipulability and stiffness) of serial manipulators, that is, under specific kinematic conditions these metrics are independent of the first and last joint angles. This property can reduce the dimensionality of the effective configuration space and simplify performance evaluation. In two scenarios—workspace performance map construction and task layout optimization—the authors claim that strategies based on JAI reduce computation and storage requirements without loss of effectiveness. The work has been accepted to the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026).
Report timeline
- Joint-Angle Invariance of Jacobian-Based Performance Indices for Serial Robotic Manipulators
The study reveals the kinematic conditions under which Jacobian-based performance indices of serial robotic manipulators, such as manipulability and stiffness, are independent of the first and last joint angles, i.e., joint-angle invariance (JAI). This property systematically reduces the dimensionality of the effective configuration space and simplifies performance evaluation. In two scenarios, workspace performance map construction and task layout optimization, the JAI strategy reduces computational effort and storage requirements without compromising effectiveness. The work has been accepted to IROS 2026.
arXiv cs.RO ·