The CMTrio-98 Sony-Legged Robot Team

Sony has provided a remarkable platform for research and development in robotic agents, namely fully autonomous legged robots. In this paper, we describe our work using Sony's legged robots to participate in the RoboCup'98 legged robot demonstration and competition. The robots are fully autonomous with on-board vision, control, and navigation. The challenges we addressed in this framework include the color calibration of the vision hardware, the landmark-based robot localization on the playing eld, and the development of robot behaviors for the actual play of the game. The paper presents our approach and contributions to these issues. We apply machine learning techniques for automated color calibration and we develop eeective vision-servoed navigation. We present our Bayesian localization algorithm. Team strategy is achieved through pre-deened behaviors. Our team of the Sony legged robots, CMTrio-98, won all of its games in the RoboCup-98 competition, and was awarded the rst place in the championship.