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In order to perform a walk on a real environment, humanoid robots need to adapt themselves to the environment, as humans do. One approach to achieve this goal is to use Machine Learning techniques that allow robots to improve their behavior with time. In this paper, we propose a system that uses Reinforcement Learning to learn the action policy that will make a robot walk in an upright position, in...
This paper describes the design and development of a new humanoid robot named Newton, that is intended for applications in research and also to be used in the Robo Cup Kid Size League World Competition. Newton robot has been designed to work without any dedicated sub-controller implemented in low level hardware, often used to control the servomotors of the robot. Newton uses only a standard personal...
This paper describes a monocular vision system for humanoid robots designed and built to compete in the Robo Cup Humanoid Kid Size League. The proposed vision system allows the robots to track a ball, identify goals, field lines, team mates and opponents, providing information such as distances and estimated location for the robots simultaneously, using threads. With experiments using the real robots...
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