In this work a new method to evolutionary robotics is proposed, it combines into asingle
framework, learning from reality and simulations. An illusory sub-system is incorporated as …

Evolutionary Robotics (ER) is a promising methodology, intended for the autonomous
development of robots, in which their behaviors are obtained as a consequence of the …

Robot learning is a growing area of research at the intersection of robotics and machine
learning. The main contributions of this paper include a review of how machine learning has …

UCHILSIM is a robotic simulator specially developed for the RoboCup four-legged league. It
reproduces with high accuracy the dynamics of AIBO motions and its interactions with the …

We describe our previous and current efforts towards achieving an unusual personal
RoboCup goal: to train a full team of robots directly through demonstration, on the field of …

Coordinating complex motion sequences remains a challenging task for robotics. Machine
Learning has aided this process, successfully improving motion sequences such as walking …

Simulation is one of the most important Tools for the development of soft-and hardware for
autonomous robots. Depending on the purpose of the simulation different levels of …

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 …

Our robotics group has teams in three leagues: humanoid, SPL, and@ home. Taking
advantage of this, we want to contribute to the transfer of relevant developments between …

This paper describes an autonomous learning method used with real robots in order to
acquire ball trapping skills in the four-legged robot league. These skills involve stopping and …