2006•The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)Open access

1A1-B11 Method for Solving Inverse Kinematics of Redundant Robot using Genetic Algorithm and Analytical Solution

Kazuya Tashiro, Seiji Aoyagi

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Abstract

It is difficult to solve inverse kinematics of an articulated redundant robot, since this problem is nonlinear. In this paper, a method for solving this problem using both genetic algorithm and analytical solution is proposed. This method is divided into three procedures; (1) making a target path from an initial pose to the goal one, (2) solving inverse kinematics by genetic algorithm for tracing this target path toward the goal pose, (3) solving inverse kinematics by an analytical method for realizing accurately the goal pose within the neighborhood of it. As a preliminary example, the effectiveness of this method is confirmed by computer simulation in case of that a 20 DOF robot passes through a hole in a thick wall.

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It is difficult to solve inverse kinematics of an articulated redundant robot, since this problem is nonlinear. In this paper, a method for solving this problem using both genetic algorithm and analytical solution is proposed. This method is divided into three procedures; (1) making a target path from an initial pose to the goal one, (2) solving inverse kinematics by genetic algorithm for tracing this target path toward the goal pose, (3) solving inverse kinematics by an analytical method for realizing accurately the goal pose within the neighborhood of it. As a preliminary example, the effectiveness of this method is confirmed by computer simulation in case of that a 20 DOF robot passes through a hole in a thick wall.

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Available abstract

It is difficult to solve inverse kinematics of an articulated redundant robot, since this problem is nonlinear. In this paper, a method for solving this problem using both genetic algorithm and analytical solution is proposed. This method is divided into three procedures; (1) making a target path from an initial pose to the goal one, (2) solving inverse kinematics by genetic algorithm for tracing this target path toward the goal pose, (3) solving inverse kinematics by an analytical method for realizing accurately the goal pose within the neighborhood of it. As a preliminary example, the effectiveness of this method is confirmed by computer simulation in case of that a 20 DOF robot passes through a hole in a thick wall.

Key concepts: Inverse kinematics, Kinematics, Genetic algorithm, Forward kinematics, Tracing, Kinematics equations, Inverse, Path (computing)

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