Improvement of multiple robots' self-localization by using perspective positional information

This study aimed to improve the precision of multiple robots' self-localization in the standard platform league of RoboCup, i.e. a robotic soccer competition. For improving the precision of the self-localization, we proposed a new technique that uses an external camera out of the field for assistance. Robots in the field use the unscented particle filter that estimates their position from some landmarks. When a robot equipped with the filter cannot recognize any landmarks exactly, particles spread and the precision of the self-localization decreases. Therefore, the overlooking camera out of the field observes each robot's position. When particles spread, the external camera estimates the foot position of the robot, and then the robot sprinkles particles on the neighborhood again. In this way, even if a robot cannot recognize landmarks exactly, assists of the external camera revise the position of particles and improve the precision.