Parameter Identification of a Robot Arm Using Genetic Algorithms

An identification method for inverse dynamics of a robot arm based on genetic algorithms (GA) is considered. It is shown that GAs are able to find robot parameters effectively even if the robot has low resolution position encoders. It is possible because the method only requires position feedback and there is no need to find out the speed and acceleration of the links that usually can only be done through finite differences calculations that cause dramatic errors during identification. The effectiveness of the algorithm is demonstrated on the example of parameter identification of the real robot PUMA 560 (for second and third links).