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首页> 外文期刊>IEEE transactions on automation science and engineering >Open-Loop Precision Grasping With Underactuated Hands Inspired by a Human Manipulation Strategy
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Open-Loop Precision Grasping With Underactuated Hands Inspired by a Human Manipulation Strategy

机译:受人为操纵策略启发的欠驱动手进行开环精确抓取

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摘要

In this paper, we demonstrate an underactuated finger design and grasping method for precision grasping and manipulation of small objects. Taking inspiration from the human grasping strategy for picking up objects from a flat surface, we introduce the flip-and-pinch task, in which the hand picks up a thin object by flipping it into a stable configuration between two fingers. Despite the fact that finger motions are not fully constrained by the hand actuators, we demonstrate that the hand and fingers can interact with the table surface to produce a set of constraints that result in a repeatable quasi-static motion trajectory. Even when utilizing only open-loop kinematic playback, this approach is shown to be robust to variation in object size and hand position. Variation of up to 20$^circ$ in orientation and 10 mm in hand height still result in experimental success rates of 80% or higher. These results suggest that the advantages of underactuated, adaptive robot hands can be carried over from basic grasping tasks to more dexterous tasks.
机译:<?Pub Dtl?>本文中,我们演示了用于精确抓握和操纵小物体的欠驱动手指设计和抓握方法。从人的抓取策略中获得灵感,从平面上拾取物体,我们引入了“翻转和捏”任务,其中手将手指翻转成两个手指之间的稳定配置来拾取物体。尽管事实上手指的运动并没有完全受到手执行器的约束,但我们证明了手和手指可以与工作台表面相互作用以产生一组约束,从而导致可重复的准静态运动轨迹。即使仅使用开环运动学回放,该方法也显示出对对象大小和手位置变化的鲁棒性。方向上最多20个 $ ^ circ $ 的变化仍然可以达到80%的实验成功率或更高。这些结果表明,操作不足的自适应机器人手的优点可以从基本的抓紧任务转移到更灵巧的任务。

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