Map building with mobile robots in dynamic environments. - Dirk Hähnel; Rudolph Triebel; Wolfram Burgard; Sebastian Thrun (ICRA, 2003)

A system for volumetric robotic mapping of abandoned mines. - Sebastian Thrun; Dirk Hähnel; David I. Ferguson; Michael Montemerlo; Rudolph Triebel; Wolfram Burgard; Christopher R. Baker; Zachary Omohundro; Scott Thayer; William Whittaker (ICRA, 2003)

Improving Simultaneous Mapping and Localization in 3D Using Global Constraints. - Rudolph Triebel; Wolfram Burgard (AAAI, 2005)

Learning Accurate Three-Dimensional Models from Range Data using Global Constraints. - Wolfram Burgard; Rudolph Triebel (GI Jahrestagung (2), 2005)

Using Hierarchical EM to Extract Planes from 3D Range Scans. - Rudolph Triebel; Wolfram Burgard; Frank Dellaert (ICRA, 2005)

Improving plane extraction from 3D data by fusing laser data and vision. - Henrik Andreasson; Rudolph Triebel; Wolfram Burgard (IROS, 2005)

Robust 3D Scan Point Classification using Associative Markov Networks. - Rudolph Triebel; Kristian Kersting; Wolfram Burgard (ICRA, 2006)

Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing. - Rudolph Triebel; Patrick Pfaff; Wolfram Burgard (IROS, 2006)

Active Monte Carlo Localization in Outdoor Terrains Using Multi-level Surface Maps. - Rainer Kümmerle; Patrick Pfaff; Rudolph Triebel; Wolfram Burgard (AMS, 2007)

Monte Carlo Localization in Outdoor Terrains Using Multi-Level Surface Maps. - Rainer Kümmerle; Rudolph Triebel; Patrick Pfaff; Wolfram Burgard (FSR, 2007)

Recovering the Shape of Objects in 3D Point Clouds with Partial Occlusions. - Rudolph Triebel; Wolfram Burgard (FSR, 2007)

Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data. - Rudolph Triebel; Óscar Martínez Mozos; Wolfram Burgard (GfKl, 2007)

Towards Mapping of Cities. - Patrick Pfaff; Rudolph Triebel; Cyrill Stachniss; Pierre Lamon; Wolfram Burgard; Roland Siegwart (ICRA, 2007)

Instace-Based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data. - Rudolph Triebel; Richard Schmidt; Óscar Martínez Mozos; Wolfram Burgard (IJCAI, 2007)

An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing. - Patrick Pfaff; Rudolph Triebel; Wolfram Burgard (Int. J. Robotics Res., 2007)

Supervised semantic labeling of places using information extracted from sensor data. - Óscar Martínez Mozos; Rudolph Triebel; Patric Jensfelt; Axel Rottmann; Wolfram Burgard (Robotics Auton. Syst., 2007)

Three-dimensional perception for mobile robots. - Rudolph Triebel (2007)

Multimodal People Detection and Tracking in Crowded Scenes. - Luciano Spinello; Rudolph Triebel; Roland Siegwart (AAAI, 2008)

Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction. - Luciano Spinello; Rudolph Triebel; Roland Siegwart (IROS, 2008)

Monte Carlo localization in outdoor terrains using multilevel surface maps. - Rainer Kümmerle; Rudolph Triebel; Patrick Pfaff; Wolfram Burgard (J. Field Robotics, 2008)

Multiclass Multimodal Detection and Tracking in Urban Environments * . - Luciano Spinello; Rudolph Triebel; Roland Siegwart (FSR, 2009)

Detecting pedestrians at very small scales. - Luciano Spinello; A. Macho; Rudolph Triebel; Roland Siegwart (IROS, 2009)

Medial Features for Superpixel Segmentation. - David Engel; Luciano Spinello; Rudolph Triebel; Roland Siegwart; Heinrich H. Bülthoff; Cristóbal Curio (MVA, 2009)

A Layered Approach to People Detection in 3D Range Data. - Luciano Spinello; Kai Oliver Arras; Rudolph Triebel; Roland Siegwart (AAAI, 2010)

Exploiting Repetitive Object Patterns for Model Compression and Completion. - Luciano Spinello; Rudolph Triebel; Dizan Vasquez; Kai Oliver Arras; Roland Siegwart (ECCV (5), 2010)

Inferring the semantics of direction signs in public places. - Jérôme Maye; Luciano Spinello; Rudolph Triebel; Roland Siegwart (ICRA, 2010)

Unsupervised discovery of repetitive objects. - Jiwon Shin; Rudolph Triebel; Roland Siegwart (ICRA, 2010)

A Bayesian Approach to Learning 3D Representations of Dynamic Environments. - Ralf Kästner; Nikolas Engelhard; Rudolph Triebel; Roland Siegwart (ISER, 2010)

Segmentation and Unsupervised Part-based Discovery of Repetitive Objects. - Rudolph Triebel; Jiwon Shin; Roland Siegwart (Robotics: Science and Systems, 2010)

Multiclass Multimodal Detection and Tracking in Urban Environments. - Luciano Spinello; Rudolph Triebel; Roland Siegwart (Int. J. Robotics Res., 2010)

Bayesian on-line learning of driving behaviors. - Jérôme Maye; Rudolph Triebel; Luciano Spinello; Roland Siegwart (ICRA, 2011)

Unsupervised 3D Object Discovery and Categorization for Mobile Robots. - Jiwon Shin; Rudolph Triebel; Roland Siegwart (ISRR, 2011)

Parsing Outdoor Scenes from Streamed 3D Laser Data Using Online Clustering and Incremental Belief Updates. - Rudolph Triebel; Rohan Paul; Daniela Rus; Paul M. Newman (AAAI, 2012)

Semantic categorization of outdoor scenes with uncertainty estimates using multi-class gaussian process classification. - Rohan Paul; Rudolph Triebel; Daniela Rus; Paul M. Newman (IROS, 2012)

Knowing when we don't know: Introspective classification for mission-critical decision making. - Hugo Grimmett; Rohan Paul; Rudolph Triebel; Ingmar Posner (ICRA, 2013)

Driven Learning for Driving: How Introspection Improves Semantic Mapping. - Rudolph Triebel; Hugo Grimmett; Rohan Paul; Ingmar Posner (ISRR, 2013)

Toward automated driving in cities using close-to-market sensors: An overview of the V-Charge Project. - Paul Timothy Furgale; Ulrich Schwesinger; Martin Rufli; Wojciech Derendarz; Hugo Grimmett; Peter Mühlfellner; Stefan Wonneberger; Julian Timpner; Stephan Rottmann; Bo Li 018; Bastian Schmidt; Thien-Nghia Nguyen; et al. (Intelligent Vehicles Symposium, 2013)

Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis. - Thomas Windheuser; Matthias Vestner; Emanuele Rodolà; Rudolph Triebel; Daniel Cremers (BMVC, 2014)

Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes. - Rudolph Triebel; Jan Stühmer; Mohamed Souiai; Daniel Cremers (GCPR, 2014)

Environment-Adaptive Learning: How Clustering Helps to Obtain Good Training Data. - Shoubhik Debnath; Shiv Sankar Baishya; Rudolph Triebel; Varun Dutt; Daniel Cremers (KI, 2014)

Two different tools for three-dimensional mapping: DE-based scan matching and feature-based loop detection. - Fernando Martín Monar; Rudolph Triebel; Luis Moreno 001; Roland Siegwart (Robotica, 2014)

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports. - Rudolph Triebel; Kai Oliver Arras; Rachid Alami 001; Lucas Beyer; Stefan Breuers; Raja Chatila 001; Mohamed Chetouani; Daniel Cremers; Vanessa Evers; Michelangelo Fiore; Hayley Hung; Omar A. Islas Ramírez; et al. (FSR, 2015)

Active online confidence boosting for efficient object classification. - Dennis Mund; Rudolph Triebel; Daniel Cremers (ICRA, 2015)

Semi-supervised online learning for efficient classification of objects in 3D data streams. - Ye Tao; Rudolph Triebel; Daniel Cremers (IROS, 2015)

Ansätze für effizientes und autonomes Lernen in Robotik und Computersehen - Rudolph Triebel (2015)

Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding. - Ioannis Chiotellis; Rudolph Triebel; Thomas Windheuser; Daniel Cremers (ECCV (2), 2016)

Stream-based Active Learning for efficient and adaptive classification of 3D objects. - Alexander Narr; Rudolph Triebel; Daniel Cremers (ICRA, 2016)

Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks. - Sahand Sharifzadeh; Ioannis Chiotellis; Rudolph Triebel; Daniel Cremers (CoRR, 2016)

Introspective classification for robot perception. - Hugo Grimmett; Rudolph Triebel; Rohan Paul; Ingmar Posner (Int. J. Robotics Res., 2016)

How Robots Learn to Classify New Objects Trained from Small Data Sets. - Tick Son Wang; Zoltan-Csaba Marton; Manuel Brucker; Rudolph Triebel (CoRL, 2017)

Experience-based optimization of robotic perception. - Maximilian Durner; Simon Kriegel; Sebastian Riedel 002; Manuel Brucker; Zoltan-Csaba Marton; Ferenc Balint-Benczedi; Rudolph Triebel (ICAR, 2017)

A method for hand-eye and camera-to-camera calibration for limited fields of view. - Christian Nissler; Zoltan-Csaba Marton; Hannes Kisner; Ulrike Thomas; Rudolph Triebel (IROS, 2017)

Selecting CNN features for online learning of 3D objects. - Monika Ullrich; Haider Ali; Maximilian Durner; Zoltan-Csaba Marton; Rudolph Triebel (IROS, 2017)

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images. - Martin Sundermeyer; Zoltan-Csaba Marton; Maximilian Durner; Manuel Brucker; Rudolph Triebel (ECCV (6), 2018)

Semantic Labeling of Indoor Environments from 3D RGB Maps. - Manuel Brucker; Maximilian Durner; Rares Ambrus; Zoltan Csaba Marton; Axel Wendt; Patric Jensfelt; Kai Oliver Arras; Rudolph Triebel (ICRA, 2018)

Incremental Semi-Supervised Learning from Streams for Object Classification. - Ioannis Chiotellis; Franziska Zimmermann; Daniel Cremers; Rudolph Triebel (IROS, 2018)

Persistent Anytime Learning of Objects from Unseen Classes. - Maximilian Denninger; Rudolph Triebel (IROS, 2018)

Appearance-Based Along-Route Localization for Planetary Missions. - Iris Lynne Grixa; Philipp Schulz; Wolfgang Stürzl; Rudolph Triebel (IROS, 2018)

6DoF Pose Estimation for Industrial Manipulation Based on Synthetic Data. - Manuel Brucker; Maximilian Durner; Zoltán-Csaba Márton; Ferenc Bálint-Benczédi; Martin Sundermeyer; Rudolph Triebel (ISER, 2018)

Simultaneous Calibration and Mapping. - Christian Nissler; Maximilian Durner; Zoltán-Csaba Márton; Rudolph Triebel (ISER, 2018)

Visual Repetition Sampling for Robot Manipulation Planning. - En Yen Puang; Peter Lehner; Zoltan-Csaba Marton; Maximilian Durner; Rudolph Triebel; Alin Albu-Schäffer (ICRA, 2019)

Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks. - Jianxiang Feng; Maximilian Durner; Zoltán-Csaba Márton; Ferenc Bálint-Benczédi; Rudolph Triebel (ISRR, 2019)

Multi-path Learning for Object Pose Estimation Across Domains. - Martin Sundermeyer; Maximilian Durner; En Yen Puang; Zoltan-Csaba Marton; Rudolph Triebel (CoRR, 2019)

A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking. - Manuel Stoiber; Martin Pfanne; Klaus H. Strobl; Rudolph Triebel; Alin Albu-Schäffer (ACCV (2), 2020)

Non-Parametric Calibration for Classification. - Jonathan Wenger; Hedvig Kjellström; Rudolph Triebel (AISTATS, 2020)

Self-Supervised Object-in-Gripper Segmentation from Robotic Motions. - Wout Boerdijk; Martin Sundermeyer; Maximilian Durner; Rudolph Triebel (CoRL, 2020)

Incremental learning of EMG-based control commands using Gaussian Processes. - Felix Schiel; Annette Hagengruber; Jörn Vogel; Rudolph Triebel (CoRL, 2020)

Information-Driven Direct RGB-D Odometry. - Alejandro Fontán; Javier Civera 001; Rudolph Triebel (CVPR, 2020)

Multi-Path Learning for Object Pose Estimation Across Domains. - Martin Sundermeyer; Maximilian Durner; En Yen Puang; Zoltan-Csaba Marton; Narunas Vaskevicius; Kai O. Arras; Rudolph Triebel (CVPR, 2020)

3D Scene Reconstruction from a Single Viewport. - Maximilian Denninger; Rudolph Triebel (ECCV (22), 2020)

Estimating Model Uncertainty of Neural Networks in Sparse Information Form. - Jongseok Lee; Matthias Humt; Jianxiang Feng; Rudolph Triebel (ICML, 2020)

Visual-Inertial Telepresence for Aerial Manipulation. - Jongseok Lee; Ribin Balachandran; Yuri S. Sarkisov; Marco De Stefano; Andre Coelho; Kashmira Shinde; Min Jun Kim 003; Rudolph Triebel; Konstantin Kondak (ICRA, 2020)

Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments. - Cedric Le Gentil; Mallikarjuna Vayugundla; Riccardo Giubilato; Wolfgang Stürzl; Teresa A. Vidal-Calleja; Rudolph Triebel (IROS, 2020)

Robust MUSIC-Based Sound Source Localization in Reverberant and Echoic Environments. - Marco Sewtz; Tim Bodenmüller; Rudolph Triebel (IROS, 2020)

Robust Vision-Based Pose Correction for a Robotic Manipulator Using Active Markers. - Lukas Meyer; Klaus H. Strobl; Rudolph Triebel (ISER, 2020)

Effective Version Space Reduction for Convolutional Neural Networks. - Jiayu Liu; Ioannis Chiotellis; Rudolph Triebel; Daniel Cremers (ECML/PKDD (2), 2020)

Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks. - Iñigo Azqueta-Gavaldon; Florian Fröhlich; Klaus H. Strobl; Rudolph Triebel (CoRR, 2020)

Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. - Anko Börner; Heinz-Wilhelm Hübers; Odej Kao; Florian Schmidt 006; Soeren Becker 001; Joachim Denzler; Daniel Matolin; David Haber; Sergio Lucia; Wojciech Samek; Rudolph Triebel; Sascha Eichstädt; et al. (CoRR, 2020)

Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry. - Kashmira Shinde; Jongseok Lee; Matthias Humt; Aydin Sezgin; Rudolph Triebel (CoRR, 2020)

Bayesian Optimization Meets Laplace Approximation for Robotic Introspection. - Matthias Humt; Jongseok Lee; Rudolph Triebel (CoRR, 2020)

Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection. - Martin Sundermeyer; Zoltan-Csaba Marton; Maximilian Durner; Rudolph Triebel (Int. J. Comput. Vis., 2020)

ARDEA - An MAV with skills for future planetary missions. - Philipp Lutz; Marcus Gerhard Müller; Moritz Maier; Samantha Stoneman; Teodor Tomic; Ingo von Bargen; Martin J. Schuster; Florian Steidle; Armin Wedler; Wolfgang Stürzl; Rudolph Triebel (J. Field Robotics, 2020)

Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras. - Riccardo Giubilato; Mallikarjuna Vayugundla; Martin J. Schuster; Wolfgang Stürzl; Armin Wedler; Rudolph Triebel; Stefano Debei (IEEE Robotics Autom. Lett., 2020)

The ARCHES Space-Analogue Demonstration Mission: Towards Heterogeneous Teams of Autonomous Robots for Collaborative Scientific Sampling in Planetary Exploration. - Martin J. Schuster; Marcus Gerhard Müller; Sebastian G. Brunner; Hannah Lehner; Peter Lehner; Ryo Sakagami; Andreas Dömel; Lukas Meyer; Bernhard Vodermayer; Riccardo Giubilato; Mallikarjuna Vayugundla; Josef Reill; et al. (IEEE Robotics Autom. Lett., 2020)

Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes. - Jongseok Lee; Jianxiang Feng; Matthias Humt; Marcus Gerhard Müller; Rudolph Triebel (CoRL, 2021)

From Evaluation to Verification: Towards Task-Oriented Relevance Metrics for Pedestrian Detection in Safety-Critical Domains. - Maria Lyssenko; Christoph Gladisch; Christian Heinzemann; Matthias Woehrle; Rudolph Triebel (CVPR Workshops, 2021)

Learning-Based Matching of 3D Submaps from Dense Stereo for Planetary-Like Environments. - Hsuan-Cheng Liao; Riccardo Giubilato; Wolfgang Stürzl; Rudolph Triebel (ICAR, 2021)

Robust Approaches for Localization on Multi-camera Systems in Dynamic Environments. - Marco Sewtz; Xiaozhou Luo; Johannes Landgraf; Tim Bodenmüller; Rudolph Triebel (ICARA, 2021)

Instance Segmentation in CARLA: Methodology and Analysis for Pedestrian-oriented Synthetic Data Generation in Crowded Scenes. - Maria Lyssenko; Christoph Gladisch; Christian Heinzemann; Matthias Woehrle; Rudolph Triebel (ICCVW, 2021)

DOT: Dynamic Object Tracking for Visual SLAM. - Irene Ballester; Alejandro Fontán; Javier Civera 001; Klaus H. Strobl; Rudolph Triebel (ICRA, 2021)

"What's This?" - Learning to Segment Unknown Objects from Manipulation Sequences. - Wout Boerdijk; Martin Sundermeyer; Maximilian Durner; Rudolph Triebel (ICRA, 2021)

Exploration of Large Outdoor Environments Using Multi-Criteria Decision Making. - Hannah Lehner; Martin J. Schuster; Tim Bodenmüller; Rudolph Triebel (ICRA, 2021)

Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes. - Martin Sundermeyer; Arsalan Mousavian; Rudolph Triebel; Dieter Fox (ICRA, 2021)

Learning to Localize in New Environments from Synthetic Training Data. - Dominik Winkelbauer; Maximilian Denninger; Rudolph Triebel (ICRA, 2021)

Unknown Object Segmentation from Stereo Images. - Maximilian Durner; Wout Boerdijk; Martin Sundermeyer; Werner Friedl; Zoltán-Csaba Márton; Rudolph Triebel (IROS, 2021)

Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps. - Riccardo Giubilato; Mallikarjuna Vayugundla; Wolfgang Stürzl; Martin J. Schuster; Armin Wedler; Rudolph Triebel (IROS, 2021)

A Photorealistic Terrain Simulation Pipeline for Unstructured Outdoor Environments. - Marcus Gerhard Müller; Maximilian Durner; Abel Gawel; Wolfgang Stürzl; Rudolph Triebel; Roland Siegwart (IROS, 2021)

Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. - Martin Wudenka; Marcus Gerhard Müller; Nikolaus Demmel; Armin Wedler; Rudolph Triebel; Daniel Cremers; Wolfgang Stürzl (IROS, 2021)

Bridging the Last Mile in Sim-to-Real Robot Perception via Bayesian Active Learning. - Jianxiang Feng; Jongseok Lee; Maximilian Durner; Rudolph Triebel (CoRR, 2021)

Making Curiosity Explicit in Vision-based RL. - Elie Aljalbout; Maximilian Ulmer; Rudolph Triebel (CoRR, 2021)

The MADMAX data set for visual-inertial rover navigation on Mars. - Lukas Meyer; Michal Smísek; Alejandro Fontan Villacampa; Laura Oliva-Maza; Daniel Medina; Martin J. Schuster; Florian Steidle; Mallikarjuna Vayugundla; Marcus Gerhard Müller; Bernhard Rebele; Armin Wedler; Rudolph Triebel (J. Field Robotics, 2021)

Regularization Strength Impact on Neural Network Ensembles. - Cedrique Rovile Njieutcheu Tassi; Anko Börner; Rudolph Triebel (ACAI, 2022)

Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects. - Manuel Stoiber; Martin Sundermeyer; Rudolph Triebel (CVPR, 2022)

Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning. - Elie Aljalbout; Maximilian Ulmer; Rudolph Triebel (ICRA, 2022)

The impact of averaging logits over probabilities on ensembles of neural networks. - Cedrique Rovile Njieutcheu Tassi; Jakob Gawlikowski; Auliya Unnisa Fitri; Rudolph Triebel (AISafety@IJCAI, 2022)

Bayesian Active Learning for Sim-to-Real Robotic Perception. - Jianxiang Feng; Jongseok Lee; Maximilian Durner; Rudolph Triebel (IROS, 2022)

RECALL: Rehearsal-free Continual Learning for Object Classification. - Markus Knauer; Maximilian Denninger; Rudolph Triebel (IROS, 2022)

Towards Safety-Aware Pedestrian Detection in Autonomous Systems. - Maria Lyssenko; Christoph Gladisch; Christian Heinzemann; Matthias Woehrle; Rudolph Triebel (IROS, 2022)

The Probabilistic Robot Kinematics Model and its Application to Sensor Fusion. - Lukas Meyer; Klaus H. Strobl; Rudolph Triebel (IROS, 2022)

A Two-stage Learning Architecture that Generates High-Quality Grasps for a Multi-Fingered Hand. - Dominik Winkelbauer; Berthold Bäuml; Matthias Humt; Nils Thuerey; Rudolph Triebel (IROS, 2022)

A Multi-body Tracking Framework - From Rigid Objects to Kinematic Structures. - Manuel Stoiber; Martin Sundermeyer; Wout Boerdijk; Rudolph Triebel (CoRR, 2022)

Virtual Reality via Object Poses and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. - Jongseok Lee; Ribin Balachandran; Konstantin Kondak; Andre Coelho; Marco De Stefano; Matthias Humt; Jianxiang Feng; Tamim Asfour; Rudolph Triebel (CoRR, 2022)

SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World. - Manuel Stoiber; Martin Pfanne; Klaus H. Strobl; Rudolph Triebel; Alin Albu-Schäffer (Int. J. Comput. Vis., 2022)

Model for Multi-View Residual Covariances Based on Perspective Deformation. - Alejandro Fontán; Laura Oliva-Maza; Javier Civera 001; Rudolph Triebel (IEEE Robotics Autom. Lett., 2022)

Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset. - Riccardo Giubilato; Wolfgang Stürzl; Armin Wedler; Rudolph Triebel (IEEE Robotics Autom. Lett., 2022)

GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps. - Riccardo Giubilato; Cedric Le Gentil; Mallikarjuna Vayugundla; Martin J. Schuster; Teresa A. Vidal-Calleja; Rudolph Triebel (Field Robotics, 2022)

Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. - Jianxiang Feng; Jongseok Lee; Simon Geisler; Stephan Günnemann; Rudolph Triebel (CoRL, 2023)

A Temporal Perspective n-Point Problem with Model Uncertainties for Cooperative Pose Estimation in a Heterogeneous Robot Team. - Florian Steidle; Simon Boche; Wolfgang Stürzl; Rudolph Triebel (ECMR, 2023)

Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. - Dominik Schnaus; Jongseok Lee; Daniel Cremers; Rudolph Triebel (ICML, 2023)

Towards a Benchmark EO Semantic Segmentation Dataset for Uncertainty Quantification. - Dawood Wasif; Yuanyuan Wang 002; Muhammad Shahzad 002; Rudolph Triebel; Xiao Xiang Zhu 001 (IGARSS, 2023)

3D Semantic Scene Reconstruction from a Single Viewport. - Maximilian Denninger; Rudolph Triebel (IMPROVE, 2023)

Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning. - Matan Atad; Jianxiang Feng; Ismael Rodríguez; Maximilian Durner; Rudolph Triebel (IROS, 2023)

Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking. - Manuel Stoiber; Mariam Elsayed; Anne E. Reichert; Florian Steidle; Dongheui Lee; Rudolph Triebel (IROS, 2023)

6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics. - Maximilian Ulmer; Maximilian Durner; Martin Sundermeyer; Manuel Stoiber; Rudolph Triebel (IROS, 2023)

Learning-Based Real-Time Torque Prediction for Grasping Unknown Objects with a Multi-Fingered Hand. - Dominik Winkelbauer; Berthold Bäuml; Rudolph Triebel (IROS, 2023)

Out-of-Distribution Detection for Adaptive Computer Vision. - Simon Kristoffersson Lind; Rudolph Triebel; Luigi Nardi; Volker Krüger (SCIA (2), 2023)

Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly. - Jianxiang Feng; Matan Atad; Ismael Rodríguez; Maximilian Durner; Stephan Günnemann; Rudolph Triebel (CoRR, 2023)

Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. - Jongseok Lee; Ribin Balachandran; Konstantin Kondak; Andre Coelho; Marco De Stefano; Matthias Humt; Jianxiang Feng; Tamim Asfour; Rudolph Triebel (Field Robotics, 2023)

BlenderProc2: A Procedural Pipeline for Photorealistic Rendering. - Maximilian Denninger; Dominik Winkelbauer; Martin Sundermeyer; Wout Boerdijk; Markus Knauer; Klaus H. Strobl; Matthias Humt; Rudolph Triebel (J. Open Source Softw., 2023)

IndoorMCD: A Benchmark for Low-Cost Multi-Camera SLAM in Indoor Environments. - Marco Sewtz; Yunis Fanger; Xiaozhou Luo; Tim Bodenmüller; Rudolph Triebel (IEEE Robotics Autom. Lett., 2023)

Learning Fluid Flow Visualizations From In-Flight Images With Tufts. - Jongseok Lee; W. F. J. Olsman; Rudolph Triebel (IEEE Robotics Autom. Lett., 2023)

An ORB-SLAM3-based Approach for Surgical Navigation in Ureteroscopy. - Laura Oliva-Maza; Florian Steidle; Julian Klodmann; Klaus H. Strobl; Rudolph Triebel (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2023)

A survey of uncertainty in deep neural networks. - Jakob Gawlikowski; Cedrique Rovile Njieutcheu Tassi; Mohsin Ali; Jongseok Lee; Matthias Humt; Jianxiang Feng; Anna M. Kruspe; Rudolph Triebel; Peter Jung 001; Ribana Roscher; Muhammad Shahzad 002; Wen Yang 001; et al. (Artif. Intell. Rev., 2023)

SID-SLAM: Semi-Direct Information-Driven RGB-D SLAM. - Alejandro Fontán; Riccardo Giubilato; Laura Oliva-Maza; Javier Civera 001; Rudolph Triebel (IEEE Robotics Autom. Lett., 2023)

Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments. - Alberto García-Hernández; Riccardo Giubilato; Klaus H. Strobl; Javier Civera 001; Rudolph Triebel (ICRA, 2024)

A Safety-Adapted Loss for Pedestrian Detection in Autonomous Driving. - Maria Lyssenko; Piyush Pimplikar; Maarten Bieshaar; Farzad Nozarian; Rudolph Triebel (ICRA, 2024)

Making the Flow Glow - Robot Perception under Severe Lighting Conditions using Normalizing Flow Gradients. - Simon Kristoffersson Lind; Rudolph Triebel; Volker Krüger (IROS, 2024)

A Learning-based Controller for Multi-Contact Grasps on Unknown Objects with a Dexterous Hand. - Dominik Winkelbauer; Rudolph Triebel; Berthold Bäuml (IROS, 2024)

A Flow-Based Credibility Metric for Safety-Critical Pedestrian Detection. - Maria Lyssenko; Christoph Gladisch; Christian Heinzemann; Matthias Woehrle; Rudolph Triebel (SAFECOMP (Workshops), 2024)

A Safety-Adapted Loss for Pedestrian Detection in Automated Driving. - Maria Lyssenko; Piyush Pimplikar; Maarten Bieshaar; Farzad Nozarian; Rudolph Triebel (CoRR, 2024)

FFHFlow: A Flow-based Variational Approach for Multi-fingered Grasp Synthesis in Real Time. - Qian Feng; Jianxiang Feng; Zhaopeng Chen; Rudolph Triebel; Alois Knoll (CoRR, 2024)

How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit? - Maximilian Ulmer; Leonard Klüpfel; Maximilian Durner; Rudolph Triebel (CoRR, 2024)

Single-Shot Metric Depth from Focused Plenoptic Cameras. - Blanca Lasheras-Hernandez; Klaus H. Strobl; Sergio Izquierdo; Tim Bodenmüller; Rudolph Triebel; Javier Civera 001 (CoRR, 2024)

Towards Explaining Uncertainty Estimates in Point Cloud Registration. - Ziyuan Qin 002; Jongseok Lee; Rudolph Triebel (CoRR, 2024)

Seeing Through Uncertainty: Robot Pose Estimation Based on Imperfect Prior Kinematic Knowledge. - Leonard Klüpfel; Lukas Burkhard; Anne E. Reichert; Maximilian Durner; Rudolph Triebel (IEEE Trans. Robotics, 2025)

Conditional Latent Diffusion Models for Zero-Shot Instance Segmentation. - Maximilian Ulmer; Wout Boerdijk; Rudolph Triebel; Maximilian Durner (CoRR, 2025)

CLEVER: Stream-Based Active Learning for Robust Semantic Perception From Human Instructions. - Jongseok Lee; Timo Birr; Rudolph Triebel; Tamim Asfour (IEEE Robotics Autom. Lett., 2025)