Improvement on Robots Positioning Accuracy Based on Genetic Algorithm

Author

Liu, Yu ; Liang, Bin ; Qiang, Wenyi ; Shu, Jiang Yan

Author_Institution

Dept. of Control Sci. & Eng., Harbin Inst. of Technol., Shenzhen

Volume

1

fYear

2006

fDate

4-6 Oct. 2006

Firstpage

387

Lastpage

392

Abstract

The paper analyzes the robot link´s positioning error sources and builds its error model of geometrical parameters. With the aid of the genetic algorithm (GA) that has the powerful global adaptive probabilistic search ability, 24 parameters of a 6-DOF robot are identified through simulation, which makes the robot´s position and orientation accuracy an great improvement. In the process of the robot calibration, stochastic measurement noises are considered. The simulation results show that with GA calibrating the robot is a kind of superior method, even if the robot link´s parameters are relative, GA still has search ability to find the optimum solution.

Keywords

genetic algorithms; position control; robots; search problems; stochastic processes; genetic algorithm; global adaptive probabilistic search ability; robot calibration; robot link positioning error sources; robots positioning accuracy; stochastic measurement noises; Calibration; End effectors; Genetic algorithms; Mathematical model; Orbital robotics; Position measurement; Robot kinematics; Robot sensing systems; Robotic assembly; Robotics and automation; Genetic Algorithm; Measurement Noises; Position and Orientation Accuracy; Robot Calibration;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Engineering in Systems Applications, IMACS Multiconference on

Conference_Location

Beijing

Print_ISBN

7-302-13922-9

Electronic_ISBN

7-900718-14-1

Type

conf

DOI

10.1109/CESA.2006.4281683

Filename

4281683