A grasping force optimization algorithm with dynamic torque constraints selection for multi-fingered robotic hands

V. Lippiello, B. Siciliano, L. Villani
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引用次数: 3

Abstract

The problem of grasping force optimization (GFO) for a multi-fingered robotic hand is considered in this paper. The GFO problem is cast in a convex optimization problem, considering also joint torque constraints. A new algorithmic solution is proposed here, which is suitable to be implemented online. The proposed formulation allows a substantial reduction of the computational load of the problem by dynamically decreasing the number of active torque constraints. Moreover, differently from other approaches, the algorithm does not require the evaluation of a new initial point at the beginning of each optimization cycle. The effectiveness of the proposed method has been tested in a simulation case study where the grasping forces of a five-fingers robotic hand are modified online to cope with time-varying external forces applied to the object.
基于动态力矩约束选择的多指机械手抓握力优化算法
研究了多指机械手的抓握力优化问题。GFO问题转化为一个考虑关节力矩约束的凸优化问题。本文提出了一种适合于在线实现的新算法。提出的公式允许通过动态减少主动扭矩约束的数量来大幅减少问题的计算负荷。此外,与其他方法不同的是,该算法不需要在每个优化周期开始时评估一个新的初始点。该方法的有效性已在一个仿真案例研究中得到验证,该案例研究在线修改了五指机械手的抓取力以应对施加在物体上的时变外力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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