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A human-like real-time grasp synthesis method for humanoid robot hands

机译:类人机器人手的类人实时抓握合成方法

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摘要

This paper addresses a real-time grasp synthesis of multi-fingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by a multi-fingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign the physical constraints of a humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics of human grasping. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables grasp posture to be changeable within 2-finger and 3-finger grasp. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our developed robot hand system by solving 2- or 3-finger grasp synthesis.
机译:本文研究了多指机器人手的实时抓握合成,以找到满足任意形状物体的力闭合条件的抓握构造。我们提出了一种针对平面多边形对象的快速有效的抓握合成算法,该算法可得出给定多边形对象上的接触位置,从而获得多指机器人手的力闭合抓握。为了获得最佳的掌握和实时计算,我们开发了偏好设置和休眠过程,并将人形手的物理约束分配给每个手指的运动。偏好由每个子层组成,每个子层反映了类似于人类针对给定目标的条件行为的原始偏好,并且它们的排列是通过人类把握的启发法来调整的。所提出的方法在牺牲全局最优性的情况下显着减少了计算时间,并使抓握姿势在两指和三指抓握内可改变。通过仿真研究评估了所提出算法的性能,从而获得具有指尖抓握力的多边形对象的力闭合抓握力。通过解决2或3指抓取综合问题,对我们开发的机器人手系统进行实验性实施,可以验证所建议的体系结构。

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