Christian Plagemann

发表

Body schema learning for robotic manipulators from visual self-perception

Wolfram Burgard, Jürgen Sturm, Christian Plagemann, 2009, Journal of Physiology - Paris.

Wolfram Burgard, Luc De Raedt, Kristian Kersting, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Real-Time Human Pose Tracking from Range Data

Sebastian Thrun, Christian Plagemann, Daphne Koller, 2012, ECCV.

Real time motion capture using a single time-of-flight camera

Sebastian Thrun, Christian Plagemann, Daphne Koller, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Look-ahead Proposals for Robust Grid-based SLAM with Rao-Blackwellized Particle Filters

Wolfram Burgard, Christian Plagemann, Giorgio Grisetti, 2009, Int. J. Robotics Res..

A Bayesian regression approach to terrain mapping and an application to legged robot locomotion

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2009 .

Vision-Based 3D Object Localization Using Probabilistic Models of Appearance

Wolfram Burgard, Christian Plagemann, Thomas Müller, 2005, DAGM-Symposium.

Modeling RFID signal strength and tag detection for localization and mapping

Wolfram Burgard, Christian Plagemann, Dominik Joho, 2009, 2009 IEEE International Conference on Robotics and Automation.

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

Wolfram Burgard, Christian Plagemann, Wendelin Feiten, 2007, GfKl.

Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2008, ECML/PKDD.

Learning predictive terrain models for legged robot locomotion

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Body Schema Learning

Wolfram Burgard, Jürgen Sturm, Christian Plagemann, 2012, Towards Service Robots for Everyday Environments.

Unsupervised body scheme learning through self-perception

Wolfram Burgard, Jürgen Sturm, Christian Plagemann, 2008, 2008 IEEE International Conference on Robotics and Automation.

Classifying dynamic objects

Wolfram Burgard, Christian Plagemann, Kai Oliver Arras, 2009, Auton. Robots.

Improved likelihood models for probabilistic localization based on range scans

Wolfram Burgard, Christian Plagemann, Patrick Pfaff, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Sequential Parameter Estimation for Fault Diagnosis in Mobile Robots Using Particle Filters

Wolfram Burgard, Christian Plagemann, W. Burgard, 2005, AMS.

Learning to transfer optimal navigation policies

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2007, Adv. Robotics.

Efficiently learning high-dimensional observation models for Monte-Carlo localization using Gaussian mixtures

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Classifying Dynamic Objects: An Unsupervised Learning Approach

Wolfram Burgard, Christian Plagemann, Kai Oliver Arras, 2008, Robotics: Science and Systems.

Learning Kinematic Models for Articulated Objects

Wolfram Burgard, Cyrill Stachniss, Kurt Konolige, 2009, IJCAI.

Planning and Failure Detection

Wolfram Burgard, Bernhard Nebel, Christian Plagemann, 2010, Cognitive Systems.

Gas Distribution Modeling using Sparse Gaussian Process Mixture Models

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2008, Robotics: Science and Systems.

Improving RFID-based indoor positioning accuracy using Gaussian processes

Wolfram Burgard, Christian Plagemann, Fernando Seco Granja, 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

Monocular range sensing: A non-parametric learning approach

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2008, 2008 IEEE International Conference on Robotics and Automation.

Most likely heteroscedastic Gaussian process regression

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2007, ICML '07.

Mapping with an Autonomous Car

Wolfram Burgard, Cyrill Stachniss, Roland Siegwart, 2006 .

Assisted Highway Lane Changing with RASCL

Sebastian Thrun, Christian Plagemann, Clifford Nass, 2010, AAAI Spring Symposium: Embedded Reasoning.

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

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2007, Robotics: Science and Systems.

Gaussian processes for flexible robot learning

Christian Plagemann, Christian Plagemann, 2008 .

Gaussian mixture models for probabilistic localization

Wolfram Burgard, Christian Plagemann, Patrick Pfaff, 2008, 2008 IEEE International Conference on Robotics and Automation.

Unsupervised discovery of object classes from range data using latent Dirichlet allocation

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2009, Robotics: Science and Systems.

A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving

Sebastian Thrun, Christian Plagemann, Andrew Y. Ng, 2010, 2010 IEEE International Conference on Robotics and Automation.

Adaptive Body Scheme Models for Robust Robotic Manipulation

Wolfram Burgard, Jürgen Sturm, Christian Plagemann, 2008, Robotics: Science and Systems.

Towards Understanding Articulated Objects

Wolfram Burgard, Cyrill Stachniss, Kurt Konolige, 2009 .

Efficient Failure Detection for Mobile Robots Using Mixed-Abstraction Particle Filters

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2006, EUROS.

Upsampling range data in dynamic environments

Sebastian Thrun, Christian Plagemann, Jongmin Baek, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

A Bayesian regression approach to terrain mapping and an application to legged robot locomotion

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2009, J. Field Robotics.

Probabilistic situation recognition for vehicular traffic scenarios

Wolfram Burgard, Christian Plagemann, Daniel Meyer-Delius, 2009, 2009 IEEE International Conference on Robotics and Automation.

Heteroscedastic Gaussian Process Regression for Modeling Range Sensors in Mobile Robotics

Wolfram Burgard, Kristian Kersting, Christian Plagemann, 2005 .

Real-time identification and localization of body parts from depth images

Sebastian Thrun, Christian Plagemann, Daphne Koller, 2010, 2010 IEEE International Conference on Robotics and Automation.

Learning gas distribution models using sparse Gaussian process mixtures

Cyrill Stachniss, Christian Plagemann, Achim J. Lilienthal, 2009, Auton. Robots.

Efficient Failure Detection on Mobile Robots Using Particle Filters with Gaussian Process Proposals

Wolfram Burgard, Dieter Fox, Christian Plagemann, 2007, IJCAI.

Estimating landmark locations from geo-referenced photographs

Wolfram Burgard, Cyrill Stachniss, Christian Plagemann, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Adaptive Non-Stationary Kernel Regression for Terrain Modeling

Wolfram Burgard, Christian Plagemann, Tobias Lang, 2007, Robotics: Science and Systems.

A nonparametric learning approach to range sensing from omnidirectional vision

Cyrill Stachniss, Christian Plagemann, Felix Endres, 2010, Robotics Auton. Syst..