Abstract
The Ulm Sparrows RoboCup team was initiated in early 1998. Among the goals of the team effort are to investigate methods for skill learning, adaptive spatial modeling, and emergent multiagent cooperation [1]. We develop both a middle-size robot league and a simulation league team. Based mostly on equipment and technology available in our robot lab, we implemented a first version of both teams for RoboCup-98 in order to gain practical experience in a major tournament. Based on the these experiences, we made significant progress in our team effort in several areas: we designed new robot hardware, extended our vision processing capabilities and implemented a revised and more complete version of our soccer agent software architecture. In particular, we added Monte Carlo localization techniques to our robots, enhanced environment modeling, and started to apply reinforcement learning techniques to improve basic playing skills.
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References
Gerhard K. Kraetzschmar, Stefan Enderle, Stefan Sablatnög, and other. The Ulm Sparrows: Research into sensorimotor integration, agency, learning, and multiagent cooperation. In Minoru Asada, editor, RoboCup-98, volume TBD of Lecture Notes in Artificial Intelligence. Springer, 1999. to appear.
Gerhard K. Kraetzschmar, Stefan Sablatnög, Stefan Enderle, and Günther Palm. Application of neurosymbolic integration of environment modeling in mobile robots. In Stefan Wermter and Ron Sun, editors, Hzbrid Neural Symbolic Integration, volume TBD of Lecture Notes in Artificial Intelligence. Springer, 1999. to appear.
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Sablatnög, S. et al. (2000). The Ulm Sparrows 99. In: Veloso, M., Pagello, E., Kitano, H. (eds) RoboCup-99: Robot Soccer World Cup III. RoboCup 1999. Lecture Notes in Computer Science(), vol 1856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45327-X_69
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DOI: https://doi.org/10.1007/3-540-45327-X_69
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