Robot gaits evolved by combining genetic algorithms and binary hill climbing
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Forces acting on a biped robot. Center of pressure-zero moment point
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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We successfully evolved a neural network controller that produces dynamic walking in a simulated bipedal robot with compliant actuators, a difficult control problem. The evolutionary evaluation uses a detailed software simulation of a physical robot. We describe: 1) a novel theoretical method to encourage populations to evolve "around" local optima, which employs multiple demes and fitness functions of progressively increasing difficulty, and 2) the novel genetic representation of the neural controller.