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Pick-Up Motion Based on Vision and Tactile Information in Hand/Arm Robot

机译:基于视觉和触觉信息的手/手臂机器人的拾取动作

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A multi-fingered robot hand receives much attention in various fields. We have developed the multi-fingered robot hand with the multi-axis force/torque sensors. For stable transportation, the robot hand must pick up an object without dropping it and places it without damaging it. This paper deals with a pick-up motion based on vision and tactile information by the eveloped robot hand. Here, the robot hand learns a posture for picking an object up by using tactile values and the visual image in advance, then determines the number of fingers in pick-up motion by the visual image. The effectiveness of the proposed grasp selection is verified through some experiments with the universal robot hand.
机译:多指机器人手在各个领域都引起了广泛关注。我们开发了带有多轴力/扭矩传感器的多指机器人手。为了稳定地运输,机械手必须拿起一个物体时不要将其掉落,并且将其放置在不会损坏的情况下。本文研究了机器人的伸手根据视觉和触觉信息进行的拾取动作。在此,机器人手预先通过使用触觉值和视觉图像来学习用于拾取物体的姿势,然后通过视觉图像来确定拾取动作中的手指的数量。通过使用通用机械手进行的一些实验验证了所提出的抓握选择的有效性。

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