Proceedings of the workshop on Computational learning theory and natural learning systems (vol. 2) : intersections between theory and experiment: intersections between theory and experiment
Evolving Hand-Eye Coordination for a Humanoid Robot with Machine Code Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Evolving a Vision-Based Line-Following Robot Controller
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Generative learning of visual concepts using multiobjective genetic programming
Pattern Recognition Letters
Learning high-level visual concepts using attributed primitives and genetic programming
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Evolution of robot controller using cartesian genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
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In this paper, we use genetic programming (GP) to evolve a vision-driven robot controller capable of navigating in a real-world environment. To this aim, we extract visual primitives from the video stream provided by a camera mounted on the robot and let them to be interpreted by a GP individual. The response of GP expressions is then used to control robot's servos. Thanks to the primitive-based approach, evolutionary process is less constrained in the process of synthesizing image features. Experiments concerning navigation in indoor environment indicate that the evolved controller performs quite well despite very limited human intervention in the design phase.