Rudolph Triebel

发表

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

Zoltan-Csaba Marton, Martin Sundermeyer, Maximilian Durner, 2018, ECCV.

From single autonomous robots toward cooperative robotic interactions for future planetary exploration missions

Uwe-Carsten Fiebig, Armin Dammann, Tamim Asfour, 2018 .

Supervised semantic labeling of places using information extracted from sensor data

Wolfram Burgard, Óscar Martínez Mozos, Rudolph Triebel, 2007, Robotics Auton. Syst..

"What's This?" - Learning to Segment Unknown Objects from Manipulation Sequences pdf

Martin Sundermeyer, Maximilian Durner, Rudolph Triebel, 2020, ArXiv.

Multimodal People Detection and Tracking in Crowded Scenes

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2008, AAAI.

Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry pdf

Rudolph Triebel, Jongseok Lee, Aydin Sezgin, 2020, ArXiv.

Active Monte Carlo Localization in Outdoor Terrains Using Multi-level Surface Maps

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2007, AMS.

A Layered Approach to People Detection in 3D Range Data

Roland Siegwart, Kai Oliver Arras, Rudolph Triebel, 2010, AAAI.

Medial Features for Superpixel Segmentation

Roland Siegwart, Heinrich H. Bülthoff, David Engel, 2009, MVA.

Parsing Outdoor Scenes from Streamed 3D Laser Data Using Online Clustering and Incremental Belief Updates

Paul Newman, Daniela Rus, Rudolph Triebel, 2012, AAAI.

A Trained System for Multimodal Perception in Urban Environments

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2009 .

Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Estimating Model Uncertainty of Neural Networks in Sparse Information Form pdf

Rudolph Triebel, Jongseok Lee, Matthias Humt, 2020, ICML.

Self-Supervised Object-in-Gripper Segmentation from Robotic Motions pdf

Martin Sundermeyer, Maximilian Durner, Rudolph Triebel, 2020, CoRL.

Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection

Zoltan-Csaba Marton, Martin Sundermeyer, Maximilian Durner, 2019, International Journal of Computer Vision.

Three-dimensional perception for mobile robots

Rudolph Triebel, Rudolph Triebel, 2008 .

Semi-supervised online learning for efficient classification of objects in 3D data streams

Daniel Cremers, Ye Tao, Rudolph Triebel, 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Bayesian Optimization Meets Laplace Approximation for Robotic Introspection pdf

Rudolph Triebel, Matthias Humt, Jongseok Lee, 2020, ArXiv.

Selecting CNN features for online learning of 3D objects

Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Improving plane extraction from 3D data by fusing laser data and vision

Wolfram Burgard, Rudolph Triebel, Henrik Andreasson, 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

The ARCHES Space-Analogue Demonstration Mission: Towards Heterogeneous Teams of Autonomous Robots for Collaborative Scientific Sampling in Planetary Exploration

Siwei Zhang, Maximilian Durner, Rudolph Triebel, 2020, IEEE Robotics and Automation Letters.

Visual-Inertial Telepresence for Aerial Manipulation

Konstantin Kondak, Rudolph Triebel, Marco De Stefano, 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

Non-Parametric Calibration for Classification

Rudolph Triebel, Hedvig Kjellström, Jonathan Wenger, 2019, AISTATS.

Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding

Daniel Cremers, Rudolph Triebel, Thomas Windheuser, 2016, ECCV.

Extraction of Dynamic Objects from Vision and Laser Data

Rudolph Triebel, Nikolas Engelhard, Ralf Kästner, 2009 .

Appearance-Based Along-Route Localization for Planetary Missions

Philipp Schulz, Rudolph Triebel, Wolfgang Stürzl, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Active online confidence boosting for efficient object classification

Daniel Cremers, Rudolph Triebel, Dennis Mund, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Uncertainty-based Classifier Adaptation for Interactive Life-long Learning

Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, 2017 .

Bayesian on-line learning of driving behaviors

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2011, 2011 IEEE International Conference on Robotics and Automation.

Driven Learning for Driving: How Introspection Improves Semantic Mapping

Rudolph Triebel, Ingmar Posner, Rohan Paul, 2016, ISRR.

Sensor Artificial Intelligence and its Application to Space Systems - A White Paper pdf

Joachim Denzler, Florian Schmidt, Wojciech Samek, 2020, ArXiv.

Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments pdf

Rudolph Triebel, Mallikarjuna Vayugundla, Teresa Vidal-Calleja, 2020, ArXiv.

Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes

Daniel Cremers, Rudolph Triebel, Mohamed Souiai, 2014, GCPR.

Map building with mobile robots in dynamic environments

Wolfram Burgard, Sebastian Thrun, Rudolph Triebel, 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

Unsupervised discovery of repetitive objects

Roland Siegwart, Rudolph Triebel, Jiwon Shin, 2010, 2010 IEEE International Conference on Robotics and Automation.

A system for volumetric robotic mapping of abandoned mines

Wolfram Burgard, William Whittaker, Sebastian Thrun, 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

Multi-Path Learning for Object Pose Estimation Across Domains

Zoltan-Csaba Marton, Martin Sundermeyer, Maximilian Durner, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Incremental Semi-Supervised Learning from Streams for Object Classification

Daniel Cremers, Rudolph Triebel, Ioannis Chiotellis, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

54 Awareness of Road Scene Participants for Autonomous Driving

Mathias Perrollaz, Christian Laugier, Rudolph Triebel, 2012 .

Machine Learning for Robotics and Computer Vision Winter term 2013 Homework Assignment 2 Topic: Regression November 15th, 2013

Rudolph Triebel, Matthias Vestner, 2013 .

Segmentation and Unsupervised Part-based Discovery of Repetitive Objects

Roland Siegwart, Rudolph Triebel, Jiwon Shin, 2010, RSS 2010.

Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2008 .

Using Hierarchical EM to Extract Planes from 3D Range Scans

Wolfram Burgard, Frank Dellaert, Rudolph Triebel, 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

Design of a Microphone Array for Rollin Justin

Rudolph Triebel, Tim Bodenmüller, Marco Sewtz, 2019 .

Non-Iterative Vision-Based Interpolation of 3D Laser Scans

Rudolph Triebel, Achim J. Lilienthal, Henrik Andreasson, 2007 .

Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis

Daniel Cremers, Rudolph Triebel, Emanuele Rodolà, 2014, BMVC.

Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras

Stefano Debei, Rudolph Triebel, Armin Wedler, 2020, IEEE Robotics and Automation Letters.

Vision based interpolation of 3D laser scans

Rudolph Triebel, Achim J. Lilienthal, Henrik Andreasson, 2006 .

GPGM-SLAM: Towards a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps

Rudolph Triebel, Mallikarjuna Vayugundla, Teresa Vidal-Calleja, 2020 .

Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks pdf

Rudolph Triebel, Klaus H. Strobl, Florian A. Fröhlich, 2020, ArXiv.

Introspective classification for robot perception

Rudolph Triebel, Ingmar Posner, Rohan Paul, 2016, Int. J. Robotics Res..

Instace-Based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data

Wolfram Burgard, Óscar Martínez Mozos, Rudolph Triebel, 2007, IJCAI.

Effective Version Space Reduction for Convolutional Neural Networks pdf

Daniel Cremers, Rudolph Triebel, Jiayu Liu, 2020, ArXiv.

InFuse: a comprehensive framework for data fusion in space robotics

Fabrice Souvannavong, Zoltan-Csaba Marton, Bilal Wehbe, 2017, ICRA 2017.

CAPTCHA Recognition with Active Deep Learning

Daniel Cremers, Rudolph Triebel, Caner Hazirbas, 2015 .

Experience-based optimization of robotic perception

Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, 2017, 2017 18th International Conference on Advanced Robotics (ICAR).

Inferring the semantics of direction signs in public places

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2010, 2010 IEEE International Conference on Robotics and Automation.

Multiclass Multimodal Detection and Tracking in Urban Environments

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2010, Int. J. Robotics Res..

Mapping with an Autonomous Car

Wolfram Burgard, Cyrill Stachniss, Roland Siegwart, 2006 .

Semantic labeling of places using information extracted from laser and vision sensor data

Wolfram Burgard, Óscar Martínez Mozos, Rudolph Triebel, 2006 .

Learning Implicit Representations of 3D Object Orientations from RGB

Zoltan-Csaba Marton, Martin Sundermeyer, Maximilian Durner, 2018 .

Segmentation and Unsupervised Part-based Discovery of Repetitive Objects

Roland Siegwart, Rudolph Triebel, Jiwon Shin, 2010, Robotics: Science and Systems.

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Daniel Cremers, Lucas Beyer, Rachid Alami, 2015, FSR.

Monte Carlo localization in outdoor terrains using multilevel surface maps

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2008, J. Field Robotics.

Towards Mapping of Cities

Wolfram Burgard, Cyrill Stachniss, Roland Siegwart, 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

Semantic categorization of outdoor scenes with uncertainty estimates using multi-class gaussian process classification

Paul Newman, Daniela Rus, Rudolph Triebel, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

ARDEA—An MAV with skills for future planetary missions

Rudolph Triebel, Armin Wedler, Marcus Gerhard Müller, 2020, J. Field Robotics.

6DoF Pose Estimation for Industrial Manipulation Based on Synthetic Data

Martin Sundermeyer, Maximilian Durner, Manuel Brucker, 2018, ISER.

An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2007, Int. J. Robotics Res..

Key technologies for intelligent and safer cars - From motion estimation to predictive collision avoidance

Roland Siegwart, Davide Scaramuzza, Rudolph Triebel, 2010, 2010 IEEE International Symposium on Industrial Electronics.

Stream-based Active Learning for efficient and adaptive classification of 3D objects

Daniel Cremers, Rudolph Triebel, Alexander Narr, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

A method for hand-eye and camera-to-camera calibration for limited fields of view

Zoltan-Csaba Marton, Rudolph Triebel, Ulrike Thomas, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Monte Carlo Localization in Outdoor Terrains Using Multi-Level Surface Maps

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2007, FSR.

Toward automated driving in cities using close-to-market sensors: An overview of the V-Charge Project

Roland Siegwart, Marc Pollefeys, Holger Mielenz, 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

Learning to Localize in New Environments from Synthetic Training Data pdf

Rudolph Triebel, Maximilian Denninger, Dominik Winkelbauer, 2020, ArXiv.

Improving Simultaneous Mapping and Localization in 3D Using Global Constraints

Wolfram Burgard, Rudolph Triebel, W. Burgard, 2005, AAAI.

Two different tools for three-dimensional mapping: DE-based scan matching and feature-based loop detection

Roland Siegwart, Luis Moreno, Rudolph Triebel, 2013, Robotica.

Semantic Labeling of Indoor Environments from 3D RGB Maps

Zoltan-Csaba Marton, Axel Wendt, Kai Oliver Arras, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

Active Monte Carlo Localization in Outdoor Terrains Using Multi-level Surface Maps

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2007, AMS.

Confidence Boosting: Improving the Introspectiveness of a Boosted Classifier for Efficient Learning

Rudolph Triebel, Ingmar Posner, Hugo Grimmett, 2013 .

Exploiting Repetitive Object Patterns for Model Compression and Completion

Roland Siegwart, Kai Oliver Arras, Rudolph Triebel, 2010, ECCV.

Robust 3D scan point classification using associative Markov networks

Wolfram Burgard, Kristian Kersting, Rudolph Triebel, 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

DOT: Dynamic Object Tracking for Visual SLAM pdf

Javier Civera, Rudolph Triebel, Klaus H. Strobl, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Persistent Anytime Learning of Objects from Unseen Classes

Rudolph Triebel, Maximilian Denninger, Rudolph Triebel, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Recovering the Shape of Objects in 3D Point Clouds with Partial Occlusions

Wolfram Burgard, Rudolph Triebel, 2007, FSR.

Learning Accurate Three-Dimensional Models from Range Data using Global Constraints

Wolfram Burgard, Rudolph Triebel, 2005, GI Jahrestagung.

InFuse : infusing perception and data fusion into space robotics with open building blocks

Fabrice Souvannavong, Zoltan-Csaba Marton, Bilal Wehbe, 2017, ICINCO 2017.

How Robots Learn to Classify New Objects Trained from Small Data Sets

Zoltan-Csaba Marton, Manuel Brucker, Rudolph Triebel, 2017, CoRL.

Information-Driven Direct RGB-D Odometry

Javier Civera, Rudolph Triebel, Alejandro Fontán, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Monte Carlo localization in outdoor terrains using multilevel surface maps

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2008 .

A Bayesian Approach to Learning 3D Representations of Dynamic Environments

Roland Siegwart, Rudolph Triebel, Ralf Kaestner, 2010, ISER.

Simultaneous Calibration and Mapping

Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel, 2018, ISER.

Unsupervised 3D Object Discovery and Categorization for Mobile Robots

Roland Siegwart, Rudolph Triebel, Jiwon Shin, 2011, ISRR.

Incremental learning of EMG-based control commands using Gaussian Processes

Rudolph Triebel, Annette Hagengruber, Jorn Vogel, 2020, CoRL.

InFuse data fusion methodology for space robotics, awareness and machine learning

Fabrice Souvannavong, Zoltan-Csaba Marton, Bilal Wehbe, 2018 .

Detecting pedestrians at very small scales

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Automated Benchmarks and Optimization of Perception Tasks

Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, 2017 .

3D Scene Reconstruction from a Single Viewport

Rudolph Triebel, Maximilian Denninger, Rudolph Triebel, 2020, ECCV.

Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing

Wolfram Burgard, Rudolph Triebel, Patrick Pfaff, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data

Wolfram Burgard, Óscar Martínez Mozos, Rudolph Triebel, 2007, GfKl.

Key Technologies for Intelligent and Safer Cars - from Motion Estimation to Predictive Motion Planning

Roland Siegwart, Davide Scaramuzza, François Pomerleau, 2009 .

Visual Repetition Sampling for Robot Manipulation Planning

Alin Albu-Schäffer, Zoltan-Csaba Marton, Maximilian Durner, 2019, 2019 International Conference on Robotics and Automation (ICRA).

Environment-Adaptive Learning: How Clustering Helps to Obtain Good Training Data

Daniel Cremers, Rudolph Triebel, Varun Dutt, 2014, KI.

Knowing when we don't know: Introspective classification for mission-critical decision making

Rudolph Triebel, Ingmar Posner, Rohan Paul, 2013, 2013 IEEE International Conference on Robotics and Automation.

Multiclass Multimodal Detection and Tracking in Urban Environments *

Roland Siegwart, Rudolph Triebel, Luciano Spinello, 2009, FSR.

A System for Three-Dimensional Robotic Mapping of Underground Mines

Wolfram Burgard, William Whittaker, Dirk Haehnel, 2002 .

Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes

Dieter Fox, Arsalan Mousavian, Martin Sundermeyer, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

From Evaluation to Verification: Towards Task-oriented Relevance Metrics for Pedestrian Detection in Safety-critical Domains

Rudolph Triebel, Matthias Woehrle, Christian Heinzemann, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps

Rudolph Triebel, Armin Wedler, Martin J. Schuster, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps pdf

Rudolph Triebel, Martin J. Schuster, Mallikarjuna Vayugundla, 2021, ArXiv.

Applying self-supervised learning for semantic cloud segmentation of all-sky images

Robert Pitz-Paal, Rudolph Triebel, Stefan Wilbert, 2021, Atmospheric Measurement Techniques.

Learning-Based Matching of 3D Submaps from Dense Stereo for Planetary-Like Environments

Rudolph Triebel, Wolfgang Stürzl, Riccardo Giubilato, 2021, 2021 20th International Conference on Advanced Robotics (ICAR).

Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions

Daniel Cremers, Rudolph Triebel, Armin Wedler, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Robust Approaches for Localization on Multi-camera Systems in Dynamic Environments

Rudolph Triebel, Tim Bodenmüller, Marco Sewtz, 2021, 2021 7th International Conference on Automation, Robotics and Applications (ICARA).

Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks pdf

Maximilian Durner, Rudolph Triebel, Zoltán-Csaba Márton, 2021, ISRR.

Learning to Localize in New Environments from Synthetic Training Data

Rudolph Triebel, Maximilian Denninger, Dominik Winkelbauer, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Exploration of Large Outdoor Environments Using Multi-Criteria Decision Making

Rudolph Triebel, Tim Bodenmüller, Martin J. Schuster, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Unknown Object Segmentation from Stereo Images

Zoltan-Csaba Marton, Werner Friedl, Martin Sundermeyer, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Bridging the Last Mile in Sim-to-Real Robot Perception via Bayesian Active Learning pdf

Maximilian Durner, Rudolph Triebel, Jongseok Lee, 2021, ArXiv.

SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World pdf

Alin Albu-Schaffer, Rudolph Triebel, Klaus H. Strobl, 2021, International Journal of Computer Vision.

The MADMAX data set for visual‐inertial rover navigation on Mars

Bernhard Rebele, Rudolph Triebel, Armin Wedler, 2021, J. Field Robotics.

Towards Heterogeneous Robotic Teams for Collaborative Scientific Sampling in Lunar and Planetary Environments

Rudolph Triebel, Andreas Dömel, Armin Wedler, 2019 .

Lifelong Learning for Mobile Robotics Applications A Half-day Workshop for IROS 2012

Rudolph Triebel, Luciano Spinello, Rudolph Triebel, 2012 .