🤖 AI Summary
Motion planning and control of cable-driven continuum robots remain challenging due to their continuous deformation, which necessitates accurate yet computationally efficient static-dynamic modeling.
Method: This paper proposes a lightweight energy-based modeling paradigm directly formulated in the actuation space. It constructs a potential energy function without explicitly modeling cable-skeleton contact interactions, integrates geometrically nonlinear beam theory to uniformly handle force/displacement inputs, and supports complex configurations—including non-uniform structures, arbitrary cable routing, and distributed loads. The model is derived from Hamilton’s principle and solved via numerical optimization combined with a semi-analytical iterative algorithm for high-fidelity forward modeling and efficient inverse kinematics.
Results: Simulation results demonstrate high accuracy, low computational latency, natural incorporation of cable elastic potential energy, and real-time controllability—establishing a unified, practical, and physically grounded static-dynamic modeling framework for continuum robots.
📝 Abstract
Continuum robots, inspired by octopus arms and elephant trunks, combine dexterity with intrinsic compliance, making them well suited for unstructured and confined environments. Yet their continuously deformable morphology poses challenges for motion planning and control, calling for accurate but lightweight models. We propose the Lightweight Actuation Space Energy Modeling (LASEM) framework for cable driven continuum robots, which formulates actuation potential energy directly in actuation space. LASEM yields an analytical forward model derived from geometrically nonlinear beam and rod theories via Hamilton's principle, while avoiding explicit modeling of cable backbone contact. It accepts both force and displacement inputs, thereby unifying kinematic and static formulations. Assuming the friction is neglected, the framework generalizes to nonuniform geometries, arbitrary cable routings, distributed loading and axial extensibility, while remaining computationally efficient for real-time use. Numerical simulations validate its accuracy, and a semi-analytical iterative scheme is developed for inverse kinematics. To address discretization in practical robots, LASEM further reformulates the functional minimization as a numerical optimization, which also naturally incorporates cable potential energy without explicit contact modeling.