人类抓取与操作背景下的机器人物体抓取

Pavel Dzitac, A. Mazid
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引用次数: 1

摘要

本文的实验和推导结果为抓取力估计提供了新的思路,从而提高了机器人在第一次尝试时抓取和操作物体接近最佳状态的机会,从而提高了机器人的物体操作灵巧性。本文提出,人体手部的物体滑动检测不是纯粹基于人体皮肤在滑动初期感知的微振动,而是基于每个手指的负载感知以及手指在握住物体时相对于其他手指的运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotic object grasping in context of human grasping and manipulation
This paper presents experimental and deductive findings that shed new light on grasp force estimation, which improves robot's chances to grasp and manipulate the object close to optimum conditions on the first attempt, which in turn improves robot's object manipulation dexterity. This paper proposes that object slippage detection in the human hand is not detected based purely on micro-vibrations sensed by the human skin during incipient slippage but also on load sensing at each finger and movement of fingers relative to each other while holding an object.
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