Issues in evolutionary robotics
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Explorations in evolutionary robotics
Adaptive Behavior
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Hi-index | 0.00 |
Hand-design of control systems for autonomous robots that act in dynamic or noisy environments is a complex task. In this paper, a new technique for controller design, termed decisionvector, is presented. An evolutionary approach is proposed: the control systems (candidate solutions) are made up of the set of robot states with respect to the obstacles it can detect, and the corresponding actions to take on each one of those situations. This initial work carries out the evolution of controllers in two environments, so that it is clear that, in spite of the simplicity of the proposed model, it is powerful enough to guide the robot to reach a target avoiding obstacles, and even, tracking a spread mark on the ground.