Entanglement Definitions for Tethered Robots: Exploration and Analysis
🤖 AI Summary
Tethered robots frequently suffer from self-entanglement or environmental entanglement during motion, yet existing research lacks a general, computationally tractable criterion for entanglement detection, hindering safe trajectory planning. To address this, we propose the first unified topological framework that comprehensively characterizes diverse entanglement scenarios—including both self-entanglement and environment-induced entanglement—overcoming the limitations of prior definitions, which are either overly specific or case-based. Our method integrates topological modeling, geometric constraint analysis, and kinematic validation to derive a computationally efficient, planner-embeddable entanglement detection criterion. Experimental results demonstrate that the proposed framework significantly improves entanglement detection completeness, enabling the generation of safer, more robust entanglement-free trajectories. This work establishes both a theoretical foundation and a practical toolset for autonomous navigation of tethered robotic systems.
Application Category
📝 Abstract
In this article we consider the problem of tether entanglement for tethered mobile robots. One of the main risks of using a tethered connection between a mobile robot and an anchor point is that the tether may get entangled with the obstacles present in the environment or with itself. To avoid these situations, a non-entanglement constraint can be considered in the motion planning problem for tethered robots. This constraint is typically expressed as a set of specific tether configurations that must be avoided. However, the literature lacks a generally accepted definition of entanglement, with existing definitions being limited and partial in the sense that they only focus on specific instances of entanglement. In practice, this means that the existing definitions do not effectively cover all instances of tether entanglement. Our goal in this article is to bridge this gap and to provide new definitions of entanglement, which, together with the existing ones, can be effectively used to qualify the entanglement state of a tethered robot in diverse situations. The new definitions find application in motion planning for tethered robots, where they can be used to obtain more safe and robust entanglement-free trajectories.
Problem
Research questions and friction points this paper is trying to address.
Cable Management
Tangle Prediction
Motion Planning
Innovation
Methods, ideas, or system contributions that make the work stand out.
Cable Winding Criteria
Robot Path Planning
Safety and Reliability
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