Trajectory Optimization for Self-Wrap-Aware Cable-Towed Planar Object Manipulation under Implicit Tension Constraints
Yu Li, Amin Fakhari, Hamid Sadeghian

TL;DR
This paper introduces a trajectory optimization framework for cable-towed planar object manipulation that accounts for self-wrap behavior and tension constraints, enabling more effective routing and force transmission.
Contribution
It formulates a routing-aware, tensioning-implicit trajectory optimization problem with a hierarchy of relaxations to handle self-wrap and tension constraints in cable-towed manipulation.
Findings
IMR exploits self-wrap for better torque application
Routing decisions can be overly conservative when explicit
Relaxation hierarchy improves tractability and solution quality
Abstract
Cable/rope elements are pervasive in deformable-object manipulation, often serving as a deformable force-transmission medium whose routing and contact determine how wrenches are delivered. In cable-towed manipulation, transmission is unilateral and hybrid: the tether can pull only when taut and becomes force-free when slack; in practice, the tether may also contact the object boundary and self-wrap around edges, which is not merely collision avoidance but a change of the wrench transmission channel by shifting the effective application point and moment arm, thereby coupling routing geometry with rigid-body motion and tensioning. We formulate self-wrap towing as a routing-aware, tensioning-implicit trajectory optimization (TITO) problem that couples (i) a tensioning-implicit taut/slack constraint and (ii) routing-conditioned transmission maps for effective length and wrench, and we build…
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Taxonomy
TopicsRobot Manipulation and Learning · Dynamics and Control of Mechanical Systems · Soft Robotics and Applications
