Layered Learning for a Soccer Legged Robot Helped with a 3D Simulator
RoboCup 2007: Robot Soccer World Cup XI
Policy gradient learning for a humanoid soccer robot
Robotics and Autonomous Systems
Policy gradient learning for quadruped soccer robots
Robotics and Autonomous Systems
LearnPNP: a tool for learning agent behaviors
RoboCup 2010
Portable autonomous walk calibration for 4-legged robots
Applied Intelligence
Perceiving forces, bumps, and touches from proprioceptive expectations
Robot Soccer World Cup XV
Real-time human-robot interactive coaching system with full-body control interface
Robot Soccer World Cup XV
Improvement of Violinist Robot using a Passive Damper Device
Journal of Intelligent and Robotic Systems
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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 been used on Sony AIBO robots and at RoboCup, with a focus on the four-legged league during the years 1998-2004. The review shows that the application-oriented use of machine learning in the four-legged league was still conservative and restricted to a few well-known and easy-to-use methods such as standard decision trees, evolutionary hill climbing, and support vector machines. Method-oriented spin-off studies emerged more frequently and increasingly addressed new and advanced machine learning techniques. Further, the paper presents some details about the growing impact of machine learning in the software system developed by the authors' robot soccer team-the NUbots