Proposal of Insertion Type Genetic Algorithm and Its Application to Based Parameter Identification for a Robot Manipulator

Abstract

The purpose of this study is the proposal of insertion type Genetic Algorithm (GA) for the based parameter identification problem of a robot manipulator. An identification problem is one of most important issues in control design for robot manipulators. Generally, the design specifications are given regarding to the controlled variables, which are the output signals of the controlled system. Therefore, it is necessary to discuss the parameter identification based on the controlled variables. However, the dynamic model of the robot manipulator has a nonlinear characteristic with respect to the controlled variables. Then we proposed a new method for the estimated physical parameters of robot manipulator using a genetic algorithm. Since a simple GA is known in some cases to fall into a local minimum and initial convergence, we propose a new GA named insertion type GA. In order to show the effectiveness of the proposed method, a study was conducted. Furthermore, through the simulations and the experiments, the physical parameters of a SICE-DD arm which is 2-DOF robot manipulator are estimated. The effectiveness of the proposed method is confirmed by the simulated results and the experimental results.