A definition of the extended Jacobian inverse kinematics algorithm for mobile robots

K. Tchoń, J. Jakubiak
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引用次数: 1

Abstract

Using control theoretic concepts we present a definitional procedure of extended Jacobian inverse kinematics algorithms for mobile robots. As a point of departure we assume a representation of the mobile robot kinematics as the end point map of a driftless control system with outputs. The space of admissible control functions of this system plays the role of the configuration space of the mobile robot, the system output space corresponds to the taskspace, so that the mobile robot kinematics transform the configuration space into the taskspace. The extended Jacobian inverse kinematics algorithm is obtained by means of the continuation method, and is based on the extended Jacobian inverse. The main step of its derivation consists in extending the original mobile robot kinematics to a map of the configuration space into itself. To this aim the configuration space is decomposed into a finite dimensional subspace, isomorphic to the taskspace, and the remaining quotient subspace. In compliance with this decomposition an augmenting kinematics map is introduced. The original kinematics and the augmenting kinematics constitute the extended kinematics. In a region free from singularities the inverse of the derivative of the extended kinematics defines the extended Jacobian inverse. By design, the extended Jacobian inverse kinematics algorithm has the property of repeatability. In the paper, the general procedure is exemplified by a derivation of the extended Jacobian inverse for a chained form system that is feedback equivalent to the kinematics of the kinematic car type mobile robot. An examination of algorithmic singularities of this algorithm is carried out. Computer simulations illustrate the performance of the algorithm.
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移动机器人扩展雅可比逆运动学算法的定义
利用控制理论的概念,给出了移动机器人扩展雅可比逆运动学算法的定义过程。作为出发点,我们将移动机器人的运动学表示为具有输出的无漂移控制系统的终点图。该系统的允许控制函数空间充当移动机器人的位形空间,系统输出空间对应于任务空间,从而使移动机器人运动学将位形空间转化为任务空间。扩展雅可比逆运动学算法是在扩展雅可比逆的基础上,采用延拓法得到的。其推导的主要步骤是将原始移动机器人运动学扩展到自身的位形空间映射。为此,将组态空间分解为与任务空间同构的有限维子空间和剩余商子空间。根据这种分解,引入了一种增广的运动学映射。原始运动学和增广运动学构成扩展运动学。在没有奇异点的区域,扩展运动学导数的逆定义扩展雅可比逆。通过设计,扩展的雅可比逆运动学算法具有可重复性。本文通过推导链式系统的扩展雅可比逆来举例说明一般方法,该系统的反馈等效于运动学小车型移动机器人的运动学。对该算法的奇异性进行了检验。计算机仿真验证了该算法的性能。
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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