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.
Bibliographical noteFunding Information:
This research was funded by Fondecyt project number 3080048. We are grateful for the great advice given by Professor Juan Carlos Letelier and the expertise in Nao programming provided by Rodrigo Palma-Amestoy as well as the kind support provided by students at Universidad de Chile’s Robotics Laboratory.
- Emergence of behavior
- Humanoid soccer robots
- Sensorimotor adaptation