Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots Via Neural Operators

Veil C, Flaschel M, Kuhl E, Santina CD (2026)

Publication Type: Journal article

Publication year: 2026

Journal

IEEE Robotics and Automation Letters IEEE

DOI: 10.1109/LRA.2026.3739023

Abstract

For fully actuated rigid robots, kinematic inversion is a purely geometric problem, efficiently solved by closed-loop inverse kinematics (CLIK) schemes that compute joint velocities to position the robot body in space. For underactuated soft robots, however, not all configurations are attainable through control action, making kinematic inversion extremely ill-posed. Extensions of CLIK address this by introducing end-to-end mappings from actuation to task space for the controller to operate on, but typically assume finite dimensions of the underlying virtual configuration space. In this work, we formulate CLIK in the infinite-dimensional domain to reason about the entire soft robot shape while solving tasks, thereby skipping intermediate approximation steps. We do this by composing an actuation-to-shape map with a shape-to-task map, deriving the differential end-to-end kinematics via an infinite-dimensional chain rule, and thereby obtaining a Jacobian-based CLIK algorithm. Since complex soft-robot models are rarely available in closed form, and neither the actuation-to-shape mapping nor its Jacobian can typically be obtained analytically, we propose to learn it using differentiable neural operator networks. We first present an analytical study on a constant-curvature segment, and then apply the neural version of the algorithm to a three-fiber soft robotic arm whose underlying model relies on morphoelasticity and active filament theory.

Authors with CRIS profile

Moritz Flaschel Lehrstuhl für Technische Mechanik (LTM) Ellen Kuhl

Involved external institutions

Stanford University

United States (USA) (US) Delft University of Technology (TU Delft)

Netherlands (NL)

How to cite

APA:

Veil, C., Flaschel, M., Kuhl, E., & Santina, C.D. (2026). Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots Via Neural Operators. IEEE Robotics and Automation Letters. https://doi.org/10.1109/LRA.2026.3739023

MLA:

Veil, Carina, et al. "Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots Via Neural Operators." IEEE Robotics and Automation Letters (2026).

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