Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Automatic definition of modular neural networks
Adaptive Behavior
Genetic programming and its application to analyze dynamical systems
Genetic programming and its application to analyze dynamical systems
The calibration index and taxonomy for robot kinematic calibration methods
International Journal of Robotics Research
Fundamentals of Manipulator Calibration
Fundamentals of Manipulator Calibration
Generalized Convergence Models for Tournament- and (mu, lambda)-Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Generation of Structured Process Models Using Genetic Programming
Selected Papers from AISB Workshop on Evolutionary Computing
Evolving computer programs without subtree crossover
IEEE Transactions on Evolutionary Computation
Base frame calibration for coordinated industrial robots
Robotics and Autonomous Systems
Coevolution in cartesian genetic programming
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
Estimating the non-linear dynamics of free-flying objects
Robotics and Autonomous Systems
Hi-index | 0.00 |
Robot calibration is a widely studied area for which a variety of solutions have been generated. Most of the methods proposed address the calibration problem by establishing a model structure followed by indirect, often ill-conditioned numeric parameter identification. This paper introduces a new inverse static kinematic calibration technique based on genetic programming, which is used to establish and identify model structure and parameters. The technique has the potential to identify the true calibration model avoiding the problems of conventional methods. The fundamentals of this approach are described and experimental results provided.