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Synthesis of dextrous manipulation by multifingered robotic hands.

机译:多指机器人手进行右旋操作的合成。

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摘要

Three most important problems in dextrous manipulation by multifingered robotic hands are the optimal grasp synthesis problem, real-time grasping force optimization problem, and coordinated manipulation with finger gaiting.; (a) Optimal grasp synthesis problem. Given an arbitrary object and the corresponding friction models, plan a set of contacts for the hand such that the grasp is force closure if such grasp exists. Moreover it is optimal in some sense. Traditional heuristic approaches, although being successfully applied to several classical manipulation examples, encounter difficulties in systems with more than 2 fingers and complex object geometries. In Chapter 3, we introduce several candidate grasp quality functions and formulate the grasp synthesis problem as a Max-transfer, a Max-normal-grasping-force, and a Min-analytic-center problem. (b) Real-time grasping force optimization problem. Given a set of contact points of the hand, the external wrench, and the corresponding friction models, determine an optimal grasping force in real-time with respect to a given objective function. In Chapter 4, we formulate the grasping force optimization as a convex optimization problem on the Riemannian manifold of positive definite matrices subject to linear constraints, for which five algorithms are developed and their respective step size selection are discussed in detail. (c)  Coordinated manipulation with finger gaiting. Given a periodic motion of the object, the geometry of the object and fingers, and the workspaces of fingers of the hand, determine if finger gaits are necessary. If that, how to plan a sequence of discrete events (fingers make or break contacts with the object) as well as the trajectories of fingers and contacts between any two events such that (1) all finger trajectories are contained in their respective workspaces; (2) at any time, whatever number of fingers are in contact with objects, the respective grasp keeps force closure. In Chapter 5, we give some preliminary results on this problem. We first use stratified configuration spaces to model the manipulation system with finger gaiting. Then, for a given gait and a periodic motion of the object, we construct two behavior basis for each finger of the hand corresponding to the contact and non-contact states. (Abstract shortened by UMI.)
机译:多指机械手进行右手操作最重要的三个问题是最佳抓握综合问题,实时抓握力优化问题手指步态的协调操作。 (a)最佳掌握综合问题。给定任意对象和相应的摩擦模型,为手计划一组接触,以便在存在这种抓地力的情况下抓地力闭合。此外,从某种意义上说它是最佳的。传统的启发式方法虽然已成功应用于几个经典的操作示例,但在具有超过2个手指和复杂对象几何体的系统中遇到了困难。在第3章中,我们介绍了几种候选抓握质量函数,并将抓握综合问题表述为最大传递,最大正法抓力和最小解析中心问题。 (b)实时抓力优化问题。给定一组手接触点,外部扳手和相应的摩擦模型,可以实时确定相对于给定目标函数的最佳抓握力。在第四章中,我们将抓力优化公式表示为正定矩阵的黎曼流形在线性约束下的凸优化问题,为此,开发了五种算法并详细讨论了它们各自的步长选择。 (c)手指步态的协调操作。给定对象的周期性运动,对象和手指的几何形状以及手的手指的工作空间,确定是否需要手指步态。如果是这样,如何计划一系列离散事件(手指与对象的接触或断开接触)以及任意两个事件之间的手指轨迹和接触轨迹,以便(1)所有手指轨迹都包含在各自的工作空间中; (2)在任何时候,无论有多少手指与物体接触,各自的抓握力都可以保持闭合力。在第5章中,我们对此问题给出了一些初步结果。我们首先使用分层配置空间通过手指步态对操纵系统进行建模。然后,对于给定的步态和对象的周期性运动,我们为手的每个手指构造了两个行为基础,分别对应于接触状态和非接触状态。 (摘要由UMI缩短。)

著录项

  • 作者

    Liu, Guanfeng.;

  • 作者单位

    Hong Kong University of Science and Technology (People's Republic of China).;

  • 授予单位 Hong Kong University of Science and Technology (People's Republic of China).;
  • 学科 Engineering Electronics and Electrical.; Engineering Mechanical.; Applied Mechanics.; Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 143 p.
  • 总页数 143
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;机械、仪表工业;应用力学;人工智能理论;
  • 关键词

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