Let Robots Play Soccer under More Natural Conditions: Experience-Based Collaborative Localization in Four-Legged League

Authors:
Qining Wang;Yan Huang;Guangming Xie;Long Wang
Affiliations:
Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China 100871;Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China 100871;Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China 100871;Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, China 100871
Venue:
RoboCup 2007: Robot Soccer World Cup XI
Year:
2008

Citing 4
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Abstract

This paper presents an experience-based collaborative approach for a group of autonomous robots to localize in asymmetric, dynamic environments. To help robots play soccer under more natural conditions, we propose a Markov localization based hybrid method with integration of environment experience construction and dynamic reference object based multi-robot localization. By using this method, the robot can estimate and correct its position perception more accurately and effectively among a group of autonomous robots, taking the odometry error and other negative influence into consideration. Satisfactory results are obtained in the RoboCup Four-Legged League environment.