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.
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© 2008 Springer-Verlag Berlin Heidelberg
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Wang, Q., Huang, Y., Xie, G., Wang, L. (2008). Let Robots Play Soccer under More Natural Conditions: Experience-Based Collaborative Localization in Four-Legged League. In: Visser, U., Ribeiro, F., Ohashi, T., Dellaert, F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science(), vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_35
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DOI: https://doi.org/10.1007/978-3-540-68847-1_35
Publisher Name: Springer, Berlin, Heidelberg
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