Abstract

A new method of kinematic analysis and singularity analysis is proposed for a 7-DOF redundant manipulator with three consecutive parallel axes. First, the redundancy angle is described according to the self-motion characteristics of the manipulator, the position and orientation of the end-effector are separated, and the inverse kinematics of this manipulator is analyzed by geometric methods with the redundancy angle as a constraint. Then, the Jacobian matrix is established to derive the conditions for the kinematic singularities of the robotic arm by using the primitive matrix method and the block matrix method. Then, the kinematic singularities conditions in the joint space are mapped to the Cartesian space, and the singular configuration is described using the end poses and redundancy angles of the robotic arm, and a singularity avoidance method based on the redundancy angles and end pose is proposed. Finally, the correctness and feasibility of the inverse kinematics algorithm and the singularity avoidance method are verified by simulation examples.

Highlights

  • With the rapid development of robotics and artificial intelligence technology, robots are increasingly used in many industrial applications, such as automobile manufacturing, mechanical processing, electrical and electronic industries, rubber and plastic industries, etc

  • The stiffness of the redundant manipulator decreases with the increase of the number of axes, so the 7-DOF manipulator, which is considered the simplest redundant manipulator, attracts the attention of scholars [2,3]

  • For redundant manipulators’ kinematic problems, a challenging problem is how to select an appropriate solution because the number of inverse kinematics solutions is infinite

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Summary

Introduction

With the rapid development of robotics and artificial intelligence technology, robots are increasingly used in many industrial applications, such as automobile manufacturing, mechanical processing, electrical and electronic industries, rubber and plastic industries, etc. To solve the singularity avoidance problem, the general methods are damped least variance (DLS) [27], singular value decomposition (SVD) [25], singular consistency method [28], and singular robustness algorithm [29] Most of these singularity avoidance algorithms are analyzed based on velocity and generally determine whether a singularity occurs during motion by computing the rank of the Jacobian matrix, while the position-based singular avoidance method in the case of deriving redundant robot inverse kinematics analytic solutions has not been discussed.

GK1 π
Singularity Analysis
Jacobian Matrix
Singularity Conditions
Singularity Avoidance
The Verification of Type II Singularity

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