@InProceedings{Soest06bnaic,
 author    = {D.A. van Soest and M. de Greef and J. Sturm and A. Visser},
 title     = {Autonomous Color Learning in an Artificial Environment},
 booktitle = {Proc. 18th Dutch-Belgian Artificial Intelligence Conference, BNAIC'06},
 address   = {Namur, Belgium},
 month     = oct,
 year      = 2006,
 pages = "299--306",
 urlpdf       = {http://www.informatik.uni-freiburg.de/~sturm/media/automaticcolorcalibrationsynopsis.pdf},
}

@InProceedings{Sturm06robocup,
 author    = {J. Sturm and P. van Rossum and A. Visser},
 title     = {Panoramic Localization in the 4-Legged League},
 booktitle = {Proc. 10th RoboCup International Symposium},
 month     = oct,
 year      = 2007,
 volume = 4434, 
 pages = "387--394",
 editor = "G. Lakemeyer and E. Sklar and D. Sorrenti and T. Takahashi",
 publisher = "Springer",
 address = "Berlin Heidelberg New York",
 urlpdf    = {http://www.informatik.uni-freiburg.de/~sturm/media/panoramiclocalization.pdf},
 note	   = "To be published in the Lecture Notes on Artificial Intelligence series, Springer Verlag, Berlin",
}


@InProceedings{Visser06bnaic,
 author    = {A. Visser and J. Sturm and F.C.A. Groen},
 title     = {Robot companion localization at home and in the office},
 booktitle = {Proc. 18th Dutch-Belgian Artificial Intelligence Conference, BNAIC'06},
 address   = {Namur, Belgium},
 pages = {347--354},
 month     = oct,
 year      = 2006,
 urlpdf       = {http://www.informatik.uni-freiburg.de/~sturm/media/panoramiclocalizationatoffice.pdf},
}


@INPROCEEDINGS{Visser06robocup-tdp,
author = {A. Visser and P. van Rossum and and J. Westra and J. Sturm and D.A. van Soest and M. de Greef},
  title = {Dutch AIBO Team at RoboCup 2006},
  year = {2006},
  month = "June",
  pdfurl = {http://www.informatik.uni-freiburg.de/~sturm/media/dat_2006_tdp.pdf},
booktitle = "Proceedings CD RoboCup 2006, Bremen, Germany",
}

@INPROCEEDINGS{Wijngaards05robocup-tdp,
author = {N. Wijngaards and F. Dignum and P. Jonker and T. de Ridder and A. Visser and S. Leijnen and J. Sturm and S. van Weers},
  title = {Dutch AIBO Team at RoboCup 2005},
  year = {2005},
  month = "July",
  pdfurl = {http://www.informatik.uni-freiburg.de/~sturm/media/dutchaiboteam_tdp_2005.pdf},
booktitle = "Proceedings CD RoboCup 2005, Osaka, Japan",
}

@TECHREPORT{Sturm05robocup-techrep,
author = "J. Sturm and A. Visser and N. Wijngaards",
title = "{D}utch {A}ibo {T}eam: Technical Report {R}obo{C}up 2005",
institution = "Dutch Aibo Team",
month = "October",
year = 2005,
howpublished = "http://www.informatik.uni-freiburg.de/~sturm/media/dat2005techreport.pdf",
}

@TECHREPORT{Visser06robocup-techrep,
author = "A. Visser and J. Sturm
and P. van Rossum
and J. Westra and Th. Bink",
title = "{D}utch {A}ibo {T}eam: Technical Report {R}obo{C}up 2006",
institution = "Dutch Aibo Team",
month = "December",
year = 2006,
howpublished =
"http://www.informatik.uni-freiburg.de/~sturm/media/dat2006techreport.pdf",
}

@InProceedings{sturm08icra,
  title     = {Unsupervised Body Scheme Learning through Self-Perception},
  author    = {Sturm, J. and Plagemann, C. and Burgard, W.},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  address   = {Pasadena, CA, USA},
  year      = {2008},
  abstract  = {In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera.  Our approach yields a compact Bayesian network for the robot's kinematic structure including the forward and inverse models relating action commands and body pose.  We propose to simultaneously learn local action models for all pairs of perceivable body parts from data generated through random ``motor babbling.''  From this repertoire of local models, we construct a Bayesian network for the full system using the pose prediction accuracy on a separate cross validation data set as the criterion for model selection.  The resulting model can be used to predict the body pose when no perception is available and allows for gradient-based posture control.  In experiments with real and simulated manipulator arms, we show that our system is able to quickly learn compact and accurate models and to robustly deal with noisy observations.},
  pdfurl    = {http://www.informatik.uni-freiburg.de/~sturm/media/sturm08icra.pdf},
  pages     = {3328--3333}
}

@InProceedings{sturm08rss,
  TITLE     = {Adaptive Body Scheme Models for Robust Robotic Manipulation},
  AUTHOR    = {Sturm, J. and Plagemann, C. and Burgard, W.},
  BOOKTITLE = {Robotics: Science and Systems (RSS)},
  ADDRESS   = {Zurich, Switzerland},
  YEAR      = {2008},
  MONTH     = {June},
  NOTE      = {To appear},
  OPTPDFURL    = {http://www.informatik.uni-freiburg.de/~sturm/media/sturm08rss.pdf},
  OPTABSTRACT  = {},
}

@InProceedings{sturm08rss-workshop,
  TITLE     = {Body Scheme Learning and Life-Long Adaptation for Robotic Manipulation},
  AUTHOR    = {Sturm, J. and Plagemann, C. and Burgard, W.},
  BOOKTITLE = {Proceedings of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS)},
  ADDRESS   = {Zurich, Switzerland},
  YEAR      = {2008},
  MONTH     = {June},
  NOTE      = {To appear},
  OPTPDFURL    = {http://www.informatik.uni-freiburg.de/~sturm/media/sturm08rss-workshop.pdf},
  OPTABSTRACT  = {},
}

@InProceedings{schulz09gwr,
  author={Hannes Schulz and Lionel Ott and Jürgen Sturm and Wolfram Burgard},
  title={Learning Kinematics from Direct Self-Observation Using Nearest-Neighbor Methods},
  conference = {Proc.~of the German Workshop on Robotics},
  year={2009}
}

@InProceedings{sturm09rss-manip,
	author = {Jürgen Sturm and Cyrill Stachniss and Vijay Pradeep and Christian Plagemann and Kurt Konolige and Wolfram Burgard},
	title = {Towards Understanding Articulated Objects},
	conference = {Proc.~of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS)},
	year = {2009}
}

@InProceedings{sturm09ijcai,
	author = {Jürgen Sturm and Vijay Pradeep and Cyrill Stachniss and Christian Plagemann and Kurt Konolige and Wolfram Burgard},
	title = {Learning  Kinematic Models for Articulated  Objects},
	conference = IJCAI,
	year = {2009},
	keywords = {robotics; machine learning; model selection},
	abstract = {Robots operating in home environments must be able to interact with articulated objects such as doors or drawers.  Ideally, robots are able to autonomously infer articulation models by observation.  In this paper, we present an approach to learn kinematic models by inferring the connectivity of rigid parts and the articulation models for the corresponding links.  Our method uses a mixture of parameterized and parameter-free (Gaussian process) representations and finds low-dimensional manifolds that provide the best explanation of the given observations.  Our approach has been implemented and evaluated using real data obtained in various realistic home environment settings.},
	url = {http://www.aaai.org/ocs/index.php/IJCAI/IJCAI-09/paper/view/408}
}

@InProceedings{meyerdel09iros,
	author = {Daniel Meyer-Delius and Jürgen Sturm and Wolfram Burgard},
	title = {Regression-Based Online Situation Recognition for Vehicular Traffic Scenarios},
	conference = IROS,
	year = {2009}
}


@article{sturm09jp,
  title = "Body schema learning for robotic manipulators from visual self-perception",
  journal = "Journal of Physiology-Paris",
  volume = "103",
  number = "3-5",
  pages = "220--231",
  year = "2009",
  note = "Neurorobotics",
  issn = "0928-4257",
  doi = "DOI: 10.1016/j.jphysparis.2009.08.005",
  url = "http://www.sciencedirect.com/science/article/B6VMC-4WY6JVM-D/2/0aaabe9b7dc9628c8c818fa87c8b56e9",
  author = "Jürgen Sturm and Christian Plagemann and Wolfram Burgard"
}