多指抓取的实时力优化算法  

REAL TIME FORCE OPTIMIZATION ALGORITHM OF MULTI-FINGERED GRASP

作　　者：姜力[1] 刘宏[1] 

机构地区：[1]哈尔滨工业大学机器人研究所,哈尔滨150001

出　　处：《机械工程学报》2007年第12期144-149,共6页Journal of Mechanical Engineering

基　　金：国家自然科学基金资助项目(60675045;50435040)

摘　　要：根据非线性摩擦约束与特定结构矩阵正定性之间的等价性,将多指抓取力规划问题描述为线性约束正定矩阵对应的平滑流形最优化问题,并且采用线性约束梯度流方法计算得到最优的抓取力。当手指数目较多时,高维描述矩阵限制了传统线性约束梯度流表达式的计算速度,为了解决该问题,基于力优化过程中描述矩阵的仿射约束特性,提出一种适合实时应用的基于抓取力矢量的线性约束梯度流算法。该算法取代描述矩阵,采用抓取力矢量表示线性约束梯度流,大大降低了线性约束梯度流表达式的维数和计算量。以摩擦点接触情况下的四指灵巧手为对象,采用该算法进行抓取力计算,分析权重因子和步距因子对于计算结果和收敛速度的影响,证明该算法的正确性和实时性。Based on the fact that nonlinear friction force limit constraints are equivalent to the positive definiteness of a certain matrix, the problem of grasping force planning for multi-fingered hand can be formulated as an optimization problem on the smooth manifold of linearly constrained positive definite matrices, and the optimal grasping force can be found by using the linear constraint gradient flow. When the number of fingers is large, high-dimensional description matrix greatly limits the calculation speed of the traditional linear constraint gradient flow. Therefore, in order to solve the problem, a grasping force vector based linear constraint gradient flow algorithm for real time applications is proposed, based on the affme constraint property of the description matrix in the optimization process. Instead of the description matrix, a grasping force vector is used to describe the linear constraint gradient flow, which greatly reduces the dimensional number and the computational cost of the linear constraint gradient flow expression. The proposed algorithm is implemented on a four-fingered dexterous hand with point friction contact model for grasping force computation. The influence of the weight factor and step factor on the computational result and the convergence speed is analyzed, and the correctness and real-time capacity of the proposed algorithm are verified.

关 键 词：多指手 力优化 梯度流 线性约束 

分 类 号：TP244[自动化与计算机技术—检测技术与自动化装置]