arXiv:2603.09557cs.RO2026-03

让缆绳自动绕物翻转,实现更精准的平面物体拖拽控制

Trajectory Optimization for Self-Wrap-Aware Cable-Towed Planar Object Manipulation under Implicit Tension Constraints

  • 通过隐式张力约束建模缆绳松紧与自缠绕,耦合运动轨迹与力传递路径
  • 隐式模式松弛法(IMR)使系统自然产生自缠绕,转向时利用重构力矩通道
  • 适合需要精准力控的柔性物体操纵场景,如机器人抓取与装配

缆绳在可变形物体操控中广泛存在,常作为力传递的柔性媒介,其布设路径与接触方式决定力矩的施加效果。在缆绳拖拽操控中,力传递具有单向性与混合特性:仅当缆绳绷紧时才能传力,松弛时则无作用力;实际中缆绳可能接触物体边界并自缠绕于边缘,这不仅是避障,更通过改变力的作用点与力臂,重构了力矩传递路径,从而将布线几何与刚体运动、张力状态紧密耦合。本文将自缠绕拖拽建模为路由感知、张力隐式的轨迹优化(TITO)问题,同时考虑(i)隐式张力的紧/松约束与(ii)依赖布线条件的等效长度与力矩映射关系,并构建从严格模式约束参考到三种可解松弛方案的层次结构:全模式松弛(FMR)、二元模式松弛(BMR)与隐式模式松弛(IMR)。在平面拖拽任务中,显式决策布线常导致保守解,靠近切换边界;而IMR通过状态演化诱导自缠绕,在转向需求时主动利用重构的扭矩通道。

原文摘要 · Abstract (English)

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 a relaxation hierarchy from a strict mode-conditioned reference to three tractable relaxations: Full-Mode Relaxation (FMR), Binary-Mode Relaxation (BMR), and Implicit-Mode Relaxation (IMR). Across planar towing tasks, we find that making routing an explicit decision often yields conservative solutions that stay near switching boundaries, whereas IMR induces self-wrap through state evolution and exploits the redirected torque channel whenever turning requires it.

缆绳操控轨迹优化自缠绕力控

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