Genetic algorithm based parameter identification for parallel manipulators

Kinematic calibration is a process in which the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. This paper presents a genetic algorithm based method of parameter identification for parallel manipulators. It removes the need to measure orientation, which is intricate and error-prone. The method using the inverse kinematics model instead of the forward one which faces more serious stability issues since it relies on a numerical solution of forward kinematics, with problematic convergence in the presence of noise is more robust because it decouple the problem into the calibration of each leg independently, and because the constraints admit an analytic form.