4.7 Article

Analytical inverse kinematic computation for 7-DOF redundant sliding manipulators

期刊

MECHANISM AND MACHINE THEORY
卷 155, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mechmachtheory.2020.104006

关键词

Redundant manipulator; Sliding manipulator; Inverse kinematics; Analytical solution; Parameterization

资金

  1. National Key R&D Program of China [2018YFB1304600]
  2. Natural Science Foundation of China [51775541]
  3. CAS Interdisciplinary Innovation Team [JCTD-2018-11]

向作者/读者索取更多资源

This study presents an analytical inverse kinematic method for rail-type redundant sliding manipulators, addressing the complexity of inverse kinematics computations. The method is universal and can solve real-time motion planning and control issues for various types of redundant sliding manipulators.
The shape and movement irregularities of rail-type redundant sliding manipulators lead to structural uncertainty, which results in inverse kinematics computations that are considerably more complicated than those of the traditional redundant manipulator currently studied. In this paper, an analytical inverse kinematic parameterized method is proposed for the redundant sliding manipulators, which solves the inverse kinematics analytically and adopts the Newton-Raphson algorithm for secondary adjustment. This paper is the first time to propose a general analytical inverse kinematics solution for all types of rail-type redundant sliding manipulators. Furthermore, the special structural characteristics of the rail-type redundant sliding manipulator are analyzed in this paper. The proposed method takes the redundant circular-sliding manipulator as the research object, and extends to all types of rail-type redundant sliding manipulators. It has the advantages of simplicity, practicability, obvious geometric meaning and universality, which can solve the real-time motion planning and control issues of all types of redundant sliding manipulators. Simulation illustrations and physical experiments are performed to verify the effectiveness and universality of the method. (C) 2020 Elsevier Ltd. All rights reserved.

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