by M Klupsch, M Lückenhaus, Cand LI Zierl, T Bandlow, M Grimme, I Kellerer and F Schwarzer
Abstract:
This paper describes the Agilo RoboCuppers - the RoboCup team of the image understanding group (FG BV) at the Technische Universität München. With a team of five Pioneer 1 robots, equipped with a CCD camera and single board computer each and coordinated by a master PC outside the field we participated in the medium size RoboCup league in Paris 1998. We use a multi-agent based approach to represent different robots and to encapsulate concurrent tasks within the robots. A fast feature extraction based on the image processing library HALCON provides the necessary data for the onboard scene interpretation. These features as well as the odometric data are checked on the master PC with regard to consistency and plausibility. The results are distributed to all robots as base for their local planning modules and also used by a coordinating global planning module.
Reference:
Agilo RoboCuppers: RoboCup Team Description (M Klupsch, M Lückenhaus, Cand LI Zierl, T Bandlow, M Grimme, I Kellerer and F Schwarzer), In Proceedings of the Second RoboCup Workshop, RoboCup-98 (M Asada, ed.), 1998.
Bibtex Entry:
@inproceedings{klupsch_agilo_1998,
author = {M Klupsch and M Lückenhaus and Cand LI Zierl and T Bandlow and M Grimme and I Kellerer and F Schwarzer},
title = {Agilo {RoboCuppers:} {RoboCup} Team Description},
booktitle = {Proceedings of the Second {RoboCup} Workshop, {RoboCup-98}},
year = {1998},
editor = {Asada, Minoru},
pages = {431–438},
address = {Paris},
month = {jul},
abstract = {This paper describes the Agilo {RoboCuppers} - the {RoboCup} team
of the image understanding group ({FG} {BV)} at the Technische Universität
München. With a team of five Pioneer 1 robots, equipped with a {CCD}
camera and single board computer each and coordinated by a master
{PC} outside the field we participated in the medium size {RoboCup}
league in Paris 1998. We use a multi-agent based approach to represent
different robots and to encapsulate concurrent tasks within the robots.
A fast feature extraction based on the image processing library {HALCON}
provides the necessary data for the onboard scene interpretation.
These features as well as the odometric data are checked on the master
{PC} with regard to consistency and plausibility. The results are
distributed to all robots as base for their local planning modules
and also used by a coordinating global planning module.},
}