Publications

ECML 2008
Nonstationary Gaussian Process Regression using Point Estimates of Local Smoothness
Christian Plagemann, Kristian Kersting, Wolfram Burgard
European Conference on Machine Learning (ECML), Antwerp, Belgium, 2008.
PDF
IAS-10 (Ed. Proc.)
Proceedings of the 10th International Conference on Intelligent Autonomous Systems
Wolfram Burgard, Rüdiger Dillmann, Christian Plagemann, Nikolaus Vahrenkamp (Editors)
Baden Baden, Germany, 2008. IOS Press.
Amazon IOS Press
IROS 2008
Learning Predictive Terrain Models for Legged Robot Locomotion
Christian Plagemann, Sebastian Mischke, Sam Prentice, Kristian Kersting, Nicholas Roy, Wolfram Burgard
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008.
PDF
IROS 2008
Efficiently Learning High-dimensional Observation Models for Monte-Carlo Localization using Gaussian Mixtures
Patrick Pfaff, Cyrill Stachniss, Christian Plagemann, Wolfram Burgard
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008.
PDF
IROS 2008
Estimating Landmark Locations from Geo-Referenced Photographs
Henrik Kretzschmar, Cyrill Stachniss, Christian Plagemann, Wolfram Burgard
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008.
PDF
RSS 2008
Adaptive Body Scheme Models for Robust Robotic Manipulation
Jürgen Sturm, Christian Plagemann, Wolfram Burgard
Robotics: Science and Systems, Zürich, Switzerland. 2008.
PDF
RSS 2008
Gas Distribution Modeling Using Sparse Gaussian Process Mixture Models
Cyrill Stachniss, Christian Plagemann, Achim Lilienthal, Wolfram Burgard
Robotics: Science and Systems, Zürich, Switzerland. 2008.
PDF
RSS 2008
Tracking and Classification of Dynamic Objects: An Unsupervised Learning Approach
Matthias Luber, Kai Arras, Christian Plagemann, Wolfram Burgard
Robotics: Science and Systems, Zürich, Switzerland. 2008.
PDF
Robotik 2008
Verteilte Software-Entwicklung in der Robotik – ein Integrations- und Testframework
Ulrich Reiser, Christoph Mies, Christian Plagemann
Robotik, München, Germany, 2008. In German.
ICRA 2008
Monocular Range Sensing: A Non-Parametric Learning Approach
Christian Plagemann, Felix Endres, Jürgen Hess, Cyrill Stachniss, Wolfram Burgard
IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 2008.
PDF
ICRA 2008
Unsupervised Body Scheme Learning through Self-Perception
Jürgen Sturm, Christian Plagemann, Wolfram Burgard
IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 2008.
PDF
ICRA 2008
Gaussian Mixture Models for Probabilistic Localization
Patrick Pfaff, Christian Plagemann, Wolfram Burgard
IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 2008.
PDF
IROS 2007
Improved Likelihood Models for Probabilistic Localization based on Range Scans
Patrick Pfaff, Christian Plagemann, Wolfram Burgard
IEEE/RSJ International Conference on Intellegent Robots and Systems (IROS), San Diego, CA, USA, 2007.
PDF
IROS 2007
Autonomous Blimp Control using Model-free Reinforcement Learning in a Continuous State and Action Space
Axel Rottmann, Christian Plagemann, Peter Hilgers, Wolfram Burgard
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, USA, 2007.
PDF
GFKL 2007
A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems
Daniel Meyer-Delius, Christian Plagemann, Georg von Wichert, Wendelin Feiten, Gisbert Lawitzky, Wolfram Burgard
German Classification Society (GfKl), Freiburg, Germany, 2007.
PDF
RSS 2007
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
Christian Plagemann, Kristian Kersting, Patrick Pfaff, Wolfram Burgard
Robotics: Science and Systems, Atlanta, GA, USA.
PDF
RSS 2007
Adaptive Non-Stationary Kernel Regression for Terrain Modeling
Tobias Lang, Christian Plagemann, Wolfram Burgard
Robotics: Science and Systems, Atlanta, GA, USA.
PDF
ICML 2007
Most Likely Heteroscedastic Gaussian Process Regression
Christian Plagemann, Kristian Kersting, Patrick Pfaff, Wolfram Burgard
ICML, Corvallis, Oregon, USA.
PDF
Advanced Robotics 2007 (Journal)
Learning to Transfer Optimal Navigation Policies
Kristian Kersting, Christian Plagemann, Alexandru Cocora, Wolfram Burgard, Luc De Raedt
Advanced Robotics. Special Issue on Imitative Robots.
FSR 2007
Look-ahead Proposals for Robust Grid-based SLAM
Slawomir Grzonka, Christian Plagemann, Giorgio Grisetti, Wolfram Burgard
FSR, Chamonix, France, 2007.
PDF

Publications

Nonstationary Gaussian Process Regression using Point Estimates of Local Smoothness

Proceedings of the 10th International Conference on Intelligent Autonomous Systems

Learning Predictive Terrain Models for Legged Robot Locomotion

Efficiently Learning High-dimensional Observation Models for Monte-Carlo Localization using Gaussian Mixtures

Estimating Landmark Locations from Geo-Referenced Photographs

Adaptive Body Scheme Models for Robust Robotic Manipulation

Gas Distribution Modeling Using Sparse Gaussian Process Mixture Models

Tracking and Classification of Dynamic Objects: An Unsupervised Learning Approach

Verteilte Software-Entwicklung in der Robotik – ein Integrations- und Testframework

Monocular Range Sensing: A Non-Parametric Learning Approach

Unsupervised Body Scheme Learning through Self-Perception

Gaussian Mixture Models for Probabilistic Localization

Improved Likelihood Models for Probabilistic Localization based on Range Scans

Autonomous Blimp Control using Model-free Reinforcement Learning in a Continuous State and Action Space

A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems

Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders

Adaptive Non-Stationary Kernel Regression for Terrain Modeling

Most Likely Heteroscedastic Gaussian Process Regression

Learning to Transfer Optimal Navigation Policies

Look-ahead Proposals for Robust Grid-based SLAM