Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Combining Simulation and Reality in Evolutionary Robotics
Journal of Intelligent and Robotic Systems
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Learning to kick the ball using back to reality
RoboCup 2004
Resilient behavior through controller self-diagnosis, adaptation and recovery
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
Humanoid robots learning to walk faster: from the real world to simulation and back
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Fast damage recovery in robotics with the T-resilience algorithm
International Journal of Robotics Research
Petri-net-based implementations for FIRA weightlifting and sprint games with a humanoid robot
Robotics and Autonomous Systems
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In this paper we discuss the applicability, potential benefits, open problems and expected contributions that an emerging set of self-modeling techniques might bring on the development of humanoid soccer robots. The idea is that robots might continuously generate, validate and adjust physical models of their sensorimotor interaction with the world. These models are exploited for adapting behavior in simulation, enhancing the learning skills of a robot with the regular transference of controllers developed in simulation to reality. Moreover, these simulations can be used to aid the execution of complex sensorimotor tasks, speed up adaptation and enhance task planning. We present experiments on the generation of behaviors for humanoid soccer robots using the Back-to-Reality algorithm. General motivations are presented, alternative algorithms are discussed and, most importantly, directions of research are proposed.