日本フィジカルAI新聞

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arXiv:2302.11428

Robotic Perception-motion Synergy for Novel Rope Wrapping Tasks

Robotic Perception-motion Synergy for Novel Rope Wrapping Tasks

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著者: Zhaoyuan Ma, Jing Xiao

分類: cs.RO

原文アブストラクト

This paper introduces a novel and general method to address the problem of using a general-purpose robot manipulator with a parallel gripper to wrap a deformable linear object (DLO), called a rope, around a rigid object, called a rod, autonomously. Such a robotic wrapping task has broad potential applications in automotive, electromechanical industries construction manufacturing, etc., but has hardly been studied. Our method does not require prior knowledge of the physical and geometrical properties of the objects but enables the robot to use real-time RGB-D perception to determine the wrapping state and feedback control to achieve high-quality results. As such, it provides the robot manipulator with the general capabilities to handle wrapping tasks of different rods or ropes. We tested our method on 6 combinations of 3 different ropes and 2 rods. The result shows that the wrapping quality improved and converged within 5 wraps for all test cases.