Abstract
When transferring manipulability across systems with different sizes and kinematic structures, matching absolute ellipsoid scale may be unnecessary when the goal is to reproduce orientation and semi-axis length ratios. Full-matrix tracking, however, penalizes both shape and absolute-scale differences, even when only shape matching is required. We therefore propose a scale-invariant manipulability shape-tracking method that treats matrices differing only by a positive scalar factor as equivalent and uses their unit-determinant representatives. We derive the differential of the unit-determinant shape representative and an orthonormal coordinate representation of the tangent tracking residual under the affine-invariant Riemannian metric (AIRM). The resulting scale-invariant objective is integrated with position and end-effector direction tasks in a constrained joint-velocity quadratic program. Simulations with four heterogeneous robots evaluate robot-to-robot and human-to-robot transfer. On three followers, the proposed method achieves endpoint shape distances of 9.30 x 10^-5 without scale tuning. With robot-specific target scales tuned during motion, the Full method retains endpoint axis-ratio errors of 0.19-0.31 on KR500 and UR20. For human reaching with concurrent tasks, the proposed method yields dual force shapes elongated along X like the human target on all four robots, with endpoint position errors of 2.4-5.6% of reference arm length versus up to 75% for the Full method tracking the original human ellipsoid.
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- Green open access
Cite this article
APA 7
Kwon, G., Lee, D. G., Li, K., Hwang, S., & Kim, W. (2026). Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators. https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators
MLA 9
Kwon, Geunwoo, et al. "Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators." https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators.
Chicago (author–date)
Kwon, Geunwoo, Dong-gyu Lee, Kai Li, Soonwoong Hwang, and Wansoo Kim. 2026. "Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators." https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators.
Harvard
Kwon, G., Lee, D. G., Li, K., Hwang, S. and Kim, W. (2026) 'Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators', Available at: https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators.
Vancouver
Kwon G, Lee DG, Li K, Hwang S, Kim W. Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators. https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators
IEEE
G. Kwon, D. G. Lee, K. Li, S. Hwang, and W. Kim, "Scale-Invariant Manipulability Shape Tracking Across Heterogeneous Manipulators," https://omanscience.com/en/articles/scale-invariant-manipulability-shape-tracking-across-heterogeneous-manipulators.