| * | 2009 |
| 23 | EE | Jürgen Sturm,
Vijay Pradeep,
Cyrill Stachniss,
Christian Plagemann,
Kurt Konolige,
Wolfram Burgard:
Learning Kinematic Models for Articulated Objects.
IJCAI 2009: 1851-1856 |
| 22 | EE | Matthias Luber,
Kai Oliver Arras,
Christian Plagemann,
Wolfram Burgard:
Classifying dynamic objects.
Auton. Robots 26(2-3): 141-151 (2009) |
| 21 | EE | Cyrill Stachniss,
Christian Plagemann,
Achim J. Lilienthal:
Learning gas distribution models using sparse Gaussian process mixtures.
Auton. Robots 26(2-3): 187-202 (2009) |
| 20 | EE | Slawomir Grzonka,
Christian Plagemann,
Giorgio Grisetti,
Wolfram Burgard:
Look-ahead Proposals for Robust Grid-based SLAM with Rao-Blackwellized Particle Filters.
I. J. Robotic Res. 28(2): 191-200 (2009) |
| 2008 |
| 19 | EE | Christian Plagemann,
Kristian Kersting,
Wolfram Burgard:
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness.
ECML/PKDD (2) 2008: 204-219 |
| 18 | EE | Jürgen Sturm,
Christian Plagemann,
Wolfram Burgard:
Unsupervised body scheme learning through self-perception.
ICRA 2008: 3328-3333 |
| 17 | EE | Patrick Pfaff,
Christian Plagemann,
Wolfram Burgard:
Gaussian mixture models for probabilistic localization.
ICRA 2008: 467-472 |
| 16 | EE | Christian Plagemann,
Felix Endres,
Juergen Michael Hess,
Cyrill Stachniss,
Wolfram Burgard:
Monocular range sensing: A non-parametric learning approach.
ICRA 2008: 929-934 |
| 15 | EE | Henrik Kretzschmar,
Cyrill Stachniss,
Christian Plagemann,
Wolfram Burgard:
Estimating landmark locations from geo-referenced photographs.
IROS 2008: 2902-2907 |
| 14 | EE | Patrick Pfaff,
Cyrill Stachniss,
Christian Plagemann,
Wolfram Burgard:
Efficiently learning high-dimensional observation models for Monte-Carlo localization using Gaussian mixtures.
IROS 2008: 3539-3544 |
| 13 | EE | Christian Plagemann,
Sebastian Mischke,
Sam Prentice,
Kristian Kersting,
Nicholas Roy,
Wolfram Burgard:
Learning predictive terrain models for legged robot locomotion.
IROS 2008: 3545-3552 |
| 2007 |
| 12 | EE | Slawomir Grzonka,
Christian Plagemann,
Giorgio Grisetti,
Wolfram Burgard:
Look-Ahead Proposals for Robust Grid-Based SLAM.
FSR 2007: 329-338 |
| 11 | EE | Daniel Meyer-Delius,
Christian Plagemann,
Georg von Wichert,
Wendelin Feiten,
Gisbert Lawitzky,
Wolfram Burgard:
A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems.
GfKl 2007: 269-276 |
| 10 | EE | Kristian Kersting,
Christian Plagemann,
Patrick Pfaff,
Wolfram Burgard:
Most likely heteroscedastic Gaussian process regression.
ICML 2007: 393-400 |
| 9 | EE | Christian Plagemann,
Dieter Fox,
Wolfram Burgard:
Efficient Failure Detection on Mobile Robots Using Particle Filters with Gaussian Process Proposals.
IJCAI 2007: 2185-2190 |
| 8 | EE | Axel Rottmann,
Christian Plagemann,
Peter Hilgers,
Wolfram Burgard:
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space.
IROS 2007: 1895-1900 |
| 7 | EE | Patrick Pfaff,
Christian Plagemann,
Wolfram Burgard:
Improved likelihood models for probabilistic localization based on range scans.
IROS 2007: 2192-2197 |
| 6 | EE | Tobias Lang,
Christian Plagemann,
Wolfram Burgard:
Adaptive Non-Stationary Kernel Regression for Terrain Modeling.
Robotics: Science and Systems 2007 |
| 5 | EE | Christian Plagemann,
Kristian Kersting,
Patrick Pfaff,
Wolfram Burgard:
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.
Robotics: Science and Systems 2007 |
| 2006 |
| 4 | EE | Christian Plagemann,
Cyrill Stachniss,
Wolfram Burgard:
Efficient Failure Detection for Mobile Robots Using Mixed-Abstraction Particle Filters.
EUROS 2006: 93-107 |
| 3 | EE | Alexandru Cocora,
Kristian Kersting,
Christian Plagemann,
Wolfram Burgard,
Luc De Raedt:
Learning Relational Navigation Policies.
IROS 2006: 2792-2797 |
| 2005 |
| 2 | EE | Christian Plagemann,
Wolfram Burgard:
Sequential Parameter Estimation for Fault Diagnosis in Mobile Robots Using Particle Filters.
AMS 2005: 197-202 |
| 1 | EE | Christian Plagemann,
Thomas Müller,
Wolfram Burgard:
Vision-Based 3D Object Localization Using Probabilistic Models of Appearance.
DAGM-Symposium 2005: 184-191 |