[Submitted on 9 Sep 2026]
Title:Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers
View a PDF of the paper titled Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers, by Thomas Cohn and 5 other authors
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Abstract:Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the configuration space, requiring special algorithmic treatment. A promising strategy is parametrizing the set of feasible configurations using analytic inverse kinematics (IK). Bespoke analytic IK functions can be written to be differentiable, a necessary property for gradient-based trajectory optimization. But the vast majority of IK functions are computed by automated meta-solvers like IKFast, and are difficult to modify for differentiability. We present a new approach for computing gradients of analytic IK parameterizations: we leverage the inverse function theorem to recover the desired gradients from the ordinary forward kinematic Jacobian. Furthermore, we present a least-squares domain extension and an optimization-amenable description of the reachability constraint, which preserves gradient signal outside the reachable workspace. We demonstrate the efficacy of our approach through numerical experiments and downstream tasks, including a hardware demonstration of an RB-Y1 picking up a box and placing it on a table. Project website: this https URL
Comments: 8 pages, 4 figures, 3 tables. Under review. Project website: this https URL
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2609.10905 [cs.RO]
(or arXiv:2609.10905v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.10905
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Thomas Cohn [view email] [v1] Wed, 9 Sep 2026 23:22:03 UTC (12,949 KB)
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