Model-Less Feedback Control of Space-based Continuum Manipulators using Backbone Tension Optimization
Shrreya Rajneesh, Nikita Pavle, Rakesh Kumar Sahoo, Manoranjan Sinha

TL;DR
This paper introduces a model-less control framework for space-based continuum manipulators that uses empirical Jacobian updates and backbone tension optimization to achieve accurate, stable, and safe manipulation without relying on complex models.
Contribution
It proposes a novel model-less control approach with real-time Jacobian refinement and tension regulation, eliminating the need for kinematic modeling and calibration.
Findings
Achieves sub-millimeter steady-state accuracy
Demonstrates smooth convergence on various trajectories
Ensures stable tension evolution and safe operation
Abstract
Continuum manipulators offer intrinsic dexterity and safe geometric compliance for navigation within confined and obstacle-rich environments. However, their infinite-dimensional backbone deformation, unmodeled internal friction, and configuration-dependent stiffness fundamentally limit the reliability of model-based kinematic formulations, resulting in inaccurate Jacobian predictions, artificial singularities, and unstable actuation behavior. Motivated by these limitations, this work presents a complete model-less control framework that bypasses kinematic modeling by using an empirically initialized Jacobian refined online through differential convex updates. Tip motion is generated via a real-time quadratic program that computes actuator increments while enforcing tendon slack avoidance and geometric limits. A backbone tension optimization term is introduced in this paper to regulate…
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Taxonomy
TopicsSoft Robotics and Applications · Dynamics and Control of Mechanical Systems · Space Satellite Systems and Control
