AGILO RoboCuppers 2001: Utility- and Plan-based Action Selection based on Probabilistically Estimated Game Situations (bibtex)
by T Schmitt, S Buck and M Beetz
Abstract:
This paper describes the AGILO RoboCuppers 1 the RoboCup team of the image understanding group (FG BV) at the Technische Universität München. a? With a team of four Pioneer I robots, all equipped with CCD camera and a single board computer, we've participated in all international middle size league tournaments from 1998 until 2001. We use a modular approach of concurrent subprograms for image processing, self localization, object tracking, action selection, path planning and basic robot control. A fast feature extraction process provides the data necessary for the on-board scene interpretation. All robot observations are fused into a single environmental model, which forms the basis for action selection, path planning and low-level robot control.
Reference:
AGILO RoboCuppers 2001: Utility- and Plan-based Action Selection based on Probabilistically Estimated Game Situations (T Schmitt, S Buck and M Beetz), In 5th International Workshop on RoboCup (Robot World Cup Soccer Games and Conferences) (P. Stone, T. Balch, G. Kraetzschmar, eds.), Springer Verlag, 2001.
Bibtex Entry:
@inproceedings{schmitt_agilo_2001, author = {T Schmitt and S Buck and M Beetz}, title = {{AGILO} {RoboCuppers} 2001: Utility- and Plan-based Action Selection based on Probabilistically Estimated Game Situations}, booktitle = {5th International Workshop on {RoboCup} (Robot World Cup Soccer Games and Conferences)}, year = {2001}, editor = {Stone, P. and Balch, T. and Kraetzschmar, G.}, series = {Lecture Notes in Computer Science}, publisher = {Springer Verlag}, abstract = {This paper describes the {AGILO} {RoboCuppers} 1 the {RoboCup} team of the image understanding group ({FG} {BV)} at the Technische Universität München. a? With a team of four Pioneer I robots, all equipped with {CCD} camera and a single board computer, we've participated in all international middle size league tournaments from 1998 until 2001. We use a modular approach of concurrent subprograms for image processing, self localization, object tracking, action selection, path planning and basic robot control. A fast feature extraction process provides the data necessary for the on-board scene interpretation. All robot observations are fused into a single environmental model, which forms the basis for action selection, path planning and low-level robot control.}, }
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