Abstract— In this paper we study online gait optimization for modular robots. The learning strategy we apply is distributed, independent on robot morphology, and easy to implemen...
David Johan Christensen, Ulrik Pagh Schultz, Kaspe...
Abstract. In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimiz...
In this work we propose an approach of incorporating learned mutation strategies (LMS) in genetic programming (GP) employed for evolution and adaptation of locomotion gaits of sim...
— In nature, animal groups achieve robustness and scalability with each individual executes a simple and adaptive strategy. Inspired by this phenomenon, we propose a decentralize...
Modular robots represent a perfect application scenario for multiagent coordination. The autonomous modules composing the robot must coordinate their respective activities to enfor...