Visual Odometry Using Sparse Bundle Adjustment on an Autonomous Outdoor Vehicle. - Niko Sünderhauf; Kurt Konolige; Simon Lacroix; Peter Protzel (AMS, 2005)

RoboKing - Bringing Robotics closer to Pupils. - Niko Sünderhauf; Thomas Krause 002; Peter Protzel (ICRA, 2005)

Bringing Robotics closer to Students - a Threefold Approach. - Niko Sünderhauf; Thomas Krause 002; Peter Protzel (ICRA, 2006)

A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments. - Sven Lange; Niko Sünderhauf; Peter Protzel (ICAR, 2009)

Using image profiles and integral images for efficient calculation of sparse optical flow fields. - Niko Sünderhauf; Peter Protzel (ICAR, 2009)

Beyond RatSLAM: Improvements to a biologically inspired SLAM system. - Niko Sünderhauf; Peter Protzel (ETFA, 2010)

The causal update filter - A novel biologically inspired filter paradigm for appearance-based SLAM. - Niko Sünderhauf; Peer Neubert; Peter Protzel (IROS, 2010)

From Neurons to Robots: Towards Efficient Biologically Inspired Filtering and SLAM. - Niko Sünderhauf; Peter Protzel (KI, 2010)

Learning from Nature: Biologically Inspired Robot Navigation and SLAM - A Review. - Niko Sünderhauf; Peter Protzel (Künstliche Intell., 2010)

BRIEF-Gist - Closing the loop by simple means. - Niko Sünderhauf; Peter Protzel (IROS, 2011)

Towards robust graphical models for GNSS-based localization in urban environments. - Niko Sünderhauf; Peter Protzel (SSD, 2012)

Towards a robust back-end for pose graph SLAM. - Niko Sünderhauf; Peter Protzel (ICRA, 2012)

Switchable constraints for robust pose graph SLAM. - Niko Sünderhauf; Peter Protzel (IROS, 2012)

Multipath mitigation in GNSS-based localization using robust optimization. - Niko Sünderhauf; Marcus Obst; Gerd Wanielik; Peter Protzel (Intelligent Vehicles Symposium, 2012)

From Saliency Based Image Features Towards Semantic Mapping. - Peer Neubert; Niko Sünderhauf; Peter Protzel (ROBOTIK, 2012)

Appearance change prediction for long-term navigation across seasons. - Peer Neubert; Niko Sünderhauf; Peter Protzel (ECMR, 2013)

Incremental smoothing vs. filtering for sensor fusion on an indoor UAV. - Sven Lange; Niko Sünderhauf; Peter Protzel (ICRA, 2013)

Switchable constraints vs. max-mixture models vs. RRR - A comparison of three approaches to robust pose graph SLAM. - Niko Sünderhauf; Peter Protzel (ICRA, 2013)

Switchable constraints and incremental smoothing for online mitigation of non-line-of-sight and multipath effects. - Niko Sünderhauf; Marcus Obst; Sven Lange; Gerd Wanielik; Peter Protzel (Intelligent Vehicles Symposium, 2013)

Fine-Grained Plant Classification Using Convolutional Neural Networks for Feature Extraction. - Niko Sünderhauf; Chris McCool; Ben Upcroft; Tristan Perez (CLEF (Working Notes), 2014)

Proceedings of the 1st Workshop on Robotics Challenges and Vision (RCV2013). - Aitor Aladren; Sasa Bodiroza; Hamid Reza Chitsaz; J. J. Guerrero; Verena V. Hafner; Kris K. Hauser; Aleksandar Jevtic; Moslem Kazemi; Bruno Lara 001; Gonzalo López-Nicolás; Peer Neubert; Peter Protzel; et al. (CoRR, 2014)

Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition. - Michael Milford; Stephanie M. Lowry; Niko Sünderhauf; Sareh Shirazi; Edward Pepperell; Ben Upcroft; Chunhua Shen; Guosheng Lin; Fayao Liu; Cesar Cadena 001; Ian D. Reid 001 (CVPR Workshops, 2015)

On the performance of ConvNet features for place recognition. - Niko Sünderhauf; Sareh Shirazi; Feras Dayoub; Ben Upcroft; Michael Milford (IROS, 2015)

Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free. - Niko Sünderhauf; Sareh Shirazi; Adam Jacobson; Feras Dayoub; Edward Pepperell; Ben Upcroft; Michael Milford (Robotics: Science and Systems, 2015)

Evaluation of Features for Leaf Classification in Challenging Conditions. - David Hall 003; Chris McCool; Feras Dayoub; Niko Sünderhauf; Ben Upcroft (WACV, 2015)

Superpixel-based appearance change prediction for long-term navigation across seasons. - Peer Neubert; Niko Sünderhauf; Peter Protzel (Robotics Auton. Syst., 2015)

Place categorization and semantic mapping on a mobile robot. - Niko Sünderhauf; Feras Dayoub; Sean McMahon; Ben Talbot; Ruth Schulz; Peter I. Corke; Gordon F. Wyeth; Ben Upcroft; Michael Milford (ICRA, 2016)

High-fidelity simulation for evaluating robotic vision performance. - John Skinner; Sourav Garg; Niko Sünderhauf; Peter I. Corke; Ben Upcroft; Michael Milford (IROS, 2016)

The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research. - Jürgen Leitner; Adam W. Tow; Jake E. Dean; Niko Sünderhauf; Joseph W. Durham; Matthew Cooper 005; Markus Eich; Christopher F. Lehnert; Ruben Mangels; Christopher McCool; Peter Kujala; Lachlan Nicholson; et al. (CoRR, 2016)

Meaningful Maps - Object-Oriented Semantic Mapping. - Niko Sünderhauf; Trung-Thanh Pham; Yasir Latif; Michael Milford; Ian D. Reid 001 (CoRR, 2016)

Visual Place Recognition: A Survey. - Stephanie M. Lowry; Niko Sünderhauf; Paul Newman 001; John J. Leonard; David D. Cox; Peter I. Corke; Michael J. Milford (IEEE Trans. Robotics, 2016)

Episode-Based Active Learning with Bayesian Neural Networks. - Feras Dayoub; Niko Sünderhauf; Peter I. Corke (CVPR Workshops, 2017)

Deep learning features at scale for visual place recognition. - Zetao Chen; Adam Jacobson; Niko Sünderhauf; Ben Upcroft; Lingqiao Liu; Chunhua Shen; Ian D. Reid 001; Michael Milford (ICRA, 2017)

The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research. - Jürgen Leitner; Adam W. Tow; Niko Sünderhauf; Jake E. Dean; Joseph W. Durham; Matthew Cooper 005; Markus Eich; Christopher F. Lehnert; Ruben Mangels; Christopher McCool; Peter T. Kujala; Lachlan Nicholson; et al. (ICRA, 2017)

Meaningful maps with object-oriented semantic mapping. - Niko Sünderhauf; Trung T. Pham; Yasir Latif; Michael Milford; Ian D. Reid 001 (IROS, 2017)

Multi-Modal Trip Hazard Affordance Detection On Construction Sites. - Sean McMahon; Niko Sünderhauf; Ben Upcroft; Michael Milford (CoRR, 2017)

What Would You Do? Acting by Learning to Predict. - Adam W. Tow; Niko Sünderhauf; Sareh Shirazi; Michael Milford; Jürgen Leitner (CoRR, 2017)

Dual Quadrics from Object Detection BoundingBoxes as Landmark Representations in SLAM. - Niko Sünderhauf; Michael Milford (CoRR, 2017)

One-Shot Reinforcement Learning for Robot Navigation with Interactive Replay. - Jake Bruce; Niko Sünderhauf; Piotr Mirowski; Raia Hadsell; Michael Milford (CoRR, 2017)

Structure Aware SLAM Using Quadrics and Planes. - Mehdi Hosseinzadeh 003; Yasir Latif; Trung Pham; Niko Sünderhauf; Ian D. Reid 001 (ACCV (3), 2018)

Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal. - Jake Bruce; Niko Sünderhauf; Piotr Mirowski; Raia Hadsell; Michael Milford (CoRL, 2018)

Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments. - Peter Anderson 001; Qi Wu 001; Damien Teney; Jake Bruce; Mark Johnson 001; Niko Sünderhauf; Ian D. Reid 001; Stephen Gould; Anton van den Hengel (CVPR, 2018)

QuadricSLAM: Dual Quadrics As SLAM Landmarks. - Lachlan Nicholson; Michael Milford; Niko Sünderhauf (CVPR Workshops, 2018)

Don't Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition. - Sourav Garg; Niko Sünderhauf; Michael Milford (ICRA, 2018)

Dropout Sampling for Robust Object Detection in Open-Set Conditions. - Dimity Miller; Lachlan Nicholson; Feras Dayoub; Niko Sünderhauf (ICRA, 2018)

SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes. - Trung T. Pham; Thanh-Toan Do; Niko Sünderhauf; Ian D. Reid 001 (ICRA, 2018)

LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics. - Sourav Garg; Niko Sünderhauf; Michael Milford (Robotics: Science and Systems, 2018)

QuadricSLAM: Constrained Dual Quadrics from Object Detections as Landmarks in Semantic SLAM. - Lachlan Nicholson; Michael Milford; Niko Sünderhauf (CoRR, 2018)

Towards Semantic SLAM: Points, Planes and Objects. - Mehdi Hosseinzadeh 003; Yasir Latif; Trung Pham; Niko Sünderhauf; Ian D. Reid 001 (CoRR, 2018)

An Orientation Factor for Object-Oriented SLAM. - Natalie Jablonsky; Michael Milford; Niko Sünderhauf (CoRR, 2018)

Zero-shot Sim-to-Real Transfer with Modular Priors. - Robert Lee; Serena Mou; Vibhavari Dasagi; Jake Bruce; Jürgen Leitner; Niko Sünderhauf (CoRR, 2018)

Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation. - David Hall 003; Feras Dayoub; John Skinner; Peter Corke; Gustavo Carneiro 001; Niko Sünderhauf (CoRR, 2018)

The limits and potentials of deep learning for robotics. - Niko Sünderhauf; Oliver Brock; Walter J. Scheirer; Raia Hadsell; Dieter Fox; Jürgen Leitner; Ben Upcroft; Pieter Abbeel; Wolfram Burgard; Michael Milford; Peter Corke (Int. J. Robotics Res., 2018)

Special issue on deep learning in robotics. - Niko Sünderhauf; Jürgen Leitner; Ben Upcroft; Nicholas Roy (Int. J. Robotics Res., 2018)

Multimodal Trip Hazard Affordance Detection on Construction Sites. - Sean McMahon; Niko Sünderhauf; Ben Upcroft; Michael Milford (IEEE Robotics Autom. Lett., 2018)

Benchmarking Sampling-based Probabilistic Object Detectors. - Dimity Miller; Niko Sünderhauf; Haoyang Zhang; David Hall 003; Feras Dayoub (CVPR Workshops, 2019)

Airborne Particle Classification in LiDAR Point Clouds Using Deep Learning. - Leo Stanislas; Julian Nubert; Daniel Dugas; Julia Nitsch; Niko Sünderhauf; Roland Siegwart; César Cadena 001; Thierry Peynot (FSR, 2019)

Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation. - Sourav Garg; Madhu Babu Vankadari; Thanuja Dharmasiri; Stephen Hausler; Niko Sünderhauf; Swagat Kumar; Tom Drummond; Michael Milford (ICRA, 2019)

Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection. - Dimity Miller; Feras Dayoub; Michael Milford; Niko Sünderhauf (ICRA, 2019)

Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors. - Quazi Marufur Rahman; Niko Sünderhauf; Feras Dayoub (IROS, 2019)

What Can Robotics Research Learn from Computer Vision Research? - Peter Corke; Feras Dayoub; David Hall 003; John Skinner; Niko Sünderhauf (ISRR, 2019)

The Probabilistic Object Detection Challenge. - John Skinner; David Hall 003; Haoyang Zhang; Feras Dayoub; Niko Sünderhauf (CoRR, 2019)

Where are the Keys? - Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional Networks. - Niko Sünderhauf (CoRR, 2019)

Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments. - Krishan Rana; Ben Talbot; Michael Milford; Niko Sünderhauf (CoRR, 2019)

A probabilistic challenge for object detection. - Niko Sünderhauf; Feras Dayoub; David Hall 003; John Skinner; Haoyang Zhang; Gustavo Carneiro 001; Peter Corke (Nat. Mach. Intell., 2019)

QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM. - Lachlan Nicholson; Michael Milford; Niko Sünderhauf (IEEE Robotics Autom. Lett., 2019)

Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments. - Krishan Rana; Ben Talbot; Vibhavari Dasagi; Michael Milford; Niko Sünderhauf (ICRA, 2020)

Multiplicative Controller Fusion: Leveraging Algorithmic Priors for Sample-efficient Reinforcement Learning and Safe Sim-To-Real Transfer. - Krishan Rana; Vibhavari Dasagi; Ben Talbot; Michael Milford; Niko Sünderhauf (IROS, 2020)

Probabilistic Object Detection: Definition and Evaluation. - David Hall 003; Feras Dayoub; John Skinner; Haoyang Zhang; Dimity Miller; Peter Corke; Gustavo Carneiro 001; Anelia Angelova; Niko Sünderhauf (WACV, 2020)

Multiplicative Controller Fusion: A Hybrid Navigation Strategy For Deployment in Unknown Environments. - Krishan Rana; Vibhavari Dasagi; Ben Talbot; Michael Milford; Niko Sünderhauf (CoRR, 2020)

Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers. - Dimity Miller; Niko Sünderhauf; Michael Milford; Feras Dayoub (CoRR, 2020)

BenchBot: Evaluating Robotics Research in Photorealistic 3D Simulation and on Real Robots. - Ben Talbot; David Hall 003; Haoyang Zhang; Suman Raj Bista; Rohan Smith; Feras Dayoub; Niko Sünderhauf (CoRR, 2020)

The Robotic Vision Scene Understanding Challenge. - David Hall 003; Ben Talbot; Suman Raj Bista; Haoyang Zhang; Rohan Smith; Feras Dayoub; Niko Sünderhauf (CoRR, 2020)

Performance Monitoring of Object Detection During Deployment. - Quazi Marufur Rahman; Niko Sünderhauf; Feras Dayoub (CoRR, 2020)

Online Monitoring of Object Detection Performance Post-Deployment. - Quazi Marufur Rahman; Niko Sünderhauf; Feras Dayoub (CoRR, 2020)

SWA Object Detection. - Haoyang Zhang; Ying Wang 074; Feras Dayoub; Niko Sünderhauf (CoRR, 2020)

Semantics for Robotic Mapping, Perception and Interaction: A Survey. - Sourav Garg; Niko Sünderhauf; Feras Dayoub; Douglas Morrison; Akansel Cosgun; Gustavo Carneiro 001; Qi Wu 001; Tat-Jun Chin; Ian D. Reid 001; Stephen Gould; Peter Corke; Michael Milford (Found. Trends Robotics, 2020)

Special Issue on Deep Learning for Robotic Vision. - Anelia Angelova; Gustavo Carneiro 001; Niko Sünderhauf; Jürgen Leitner (Int. J. Comput. Vis., 2020)

VarifocalNet: An IoU-Aware Dense Object Detector. - Haoyang Zhang; Ying Wang 074; Feras Dayoub; Niko Sünderhauf (CVPR, 2021)

Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM. - Suman Raj Bista; David Hall 003; Ben Talbot; Haoyang Zhang; Feras Dayoub; Niko Sünderhauf (IROS, 2021)

Online Monitoring of Object Detection Performance During Deployment. - Quazi Marufur Rahman; Niko Sünderhauf; Feras Dayoub (IROS, 2021)

Critic Guided Segmentation of Rewarding Objects in First-Person Views. - Andrew Melnik; Augustin Harter; Christian Limberg; Krishan Rana; Niko Sünderhauf; Helge J. Ritter (KI, 2021)

Class Anchor Clustering: A Loss for Distance-based Open Set Recognition. - Dimity Miller; Niko Sünderhauf; Michael Milford; Feras Dayoub (WACV, 2021)

Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment. - Quazi Marufur Rahman; Niko Sünderhauf; Feras Dayoub (WACV (Workshops), 2021)

Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots. - Krishan Rana; Vibhavari Dasagi; Jesse Haviland; Ben Talbot; Michael Milford; Niko Sünderhauf (CoRR, 2021)

Hyperdimensional Feature Fusion for Out-Of-Distribution Detection. - Samuel Wilson; Niko Sünderhauf; Feras Dayoub (CoRR, 2021)

Probabilistic Visual Place Recognition for Hierarchical Localization. - Ming Xu 015; Niko Sünderhauf; Michael Milford (IEEE Robotics Autom. Lett., 2021)

Corrections to "Probabilistic Visual Place Recognition for Hierarchical Localization". - Ming Xu 015; Niko Sünderhauf; Michael Milford (IEEE Robotics Autom. Lett., 2021)

Probabilistic Appearance-Invariant Topometric Localization With New Place Awareness. - Ming Xu 015; Tobias Fischer 001; Niko Sünderhauf; Michael Milford (IEEE Robotics Autom. Lett., 2021)

Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics. - Krishan Rana; Ming Xu 015; Brendan Tidd; Michael Milford; Niko Sünderhauf (CoRL, 2022)

Forest Traversability Mapping (FTM): Traversability estimation using 3D voxel-based Normal Distributed Transform to enable forest navigation. - Fabio Ruetz; Paulo Vinicius Koerich Borges; Niko Sünderhauf; Emili Hernández; Thierry Peynot (IROS, 2022)

Implicit Object Mapping With Noisy Data. - Jad Abou-Chakra; Feras Dayoub; Niko Sünderhauf (CoRR, 2022)

Noisy Inliers Make Great Outliers: Out-of-Distribution Object Detection with Noisy Synthetic Outliers. - Samuel Wilson; Tobias Fischer 001; Feras Dayoub; Niko Sünderhauf (CoRR, 2022)

Retrospectives on the Embodied AI Workshop. - Matt Deitke; Dhruv Batra; Yonatan Bisk; Tommaso Campari; Angel X. Chang; Devendra Singh Chaplot; Changan Chen; Claudia Pérez-D'Arpino; Kiana Ehsani; Ali Farhadi; Li Fei-Fei 001; Anthony G. Francis; et al. (CoRR, 2022)

ParticleNeRF: A Particle-Based Encoding for Online Neural Radiance Fields in Dynamic Scenes. - Jad Abou-Chakra; Feras Dayoub; Niko Sünderhauf (CoRR, 2022)

Semantic-geometric visual place recognition: a new perspective for reconciling opposing views. - Sourav Garg; Niko Sünderhauf; Michael Milford (Int. J. Robotics Res., 2022)

BenchBot environments for active robotics (BEAR): Simulated data for active scene understanding research. - David Hall 003; Ben Talbot; Suman Raj Bista; Haoyang Zhang; Rohan Smith; Feras Dayoub; Niko Sünderhauf (Int. J. Robotics Res., 2022)

A Holistic Approach to Reactive Mobile Manipulation. - Jesse Haviland; Niko Sünderhauf; Peter Corke (IEEE Robotics Autom. Lett., 2022)

Uncertainty for Identifying Open-Set Errors in Visual Object Detection. - Dimity Miller; Niko Sünderhauf; Michael Milford; Feras Dayoub (IEEE Robotics Autom. Lett., 2022)

FSNet: A Failure Detection Framework for Semantic Segmentation. - Quazi Marufur Rahman; Niko Sünderhauf; Peter Corke; Feras Dayoub (IEEE Robotics Autom. Lett., 2022)

SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning. - Krishan Rana; Jesse Haviland; Sourav Garg; Jad Abou-Chakra; Ian D. Reid 001; Niko Sünderhauf (CoRL, 2023)

SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection. - Samuel Wilson; Tobias Fischer 001; Feras Dayoub; Dimity Miller; Niko Sünderhauf (ICCV, 2023)

Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields. - Niko Sünderhauf; Jad Abou-Chakra; Dimity Miller (ICRA, 2023)

Hyperdimensional Feature Fusion for Out-of-Distribution Detection. - Samuel Wilson; Tobias Fischer 001; Niko Sünderhauf; Feras Dayoub (WACV, 2023)

Addressing the Challenges of Open-World Object Detection. - David Pershouse; Feras Dayoub; Dimity Miller; Niko Sünderhauf (CoRR, 2023)

The Need for Inherently Privacy-Preserving Vision in Trustworthy Autonomous Systems. - Adam K. Taras; Niko Sünderhauf; Peter Corke; Donald G. Dansereau (CoRR, 2023)

Contrastive Language, Action, and State Pre-training for Robot Learning. - Krishan Rana; Andrew Melnik; Niko Sünderhauf (CoRR, 2023)

SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Task Planning. - Krishan Rana; Jesse Haviland; Sourav Garg; Jad Abou-Chakra; Ian D. Reid 001; Niko Sünderhauf (CoRR, 2023)

LHManip: A Dataset for Long-Horizon Language-Grounded Manipulation Tasks in Cluttered Tabletop Environments. - Federico Ceola; Lorenzo Natale; Niko Sünderhauf; Krishan Rana (CoRR, 2023)

Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localization - Niko Sünderhauf (Springer, 2023)

Bayesian controller fusion: Leveraging control priors in deep reinforcement learning for robotics. - Krishan Rana; Vibhavari Dasagi; Jesse Haviland; Ben Talbot; Michael Milford; Niko Sünderhauf (Int. J. Robotics Res., 2023)

Physically Embodied Gaussian Splatting: A Visually Learnt and Physically Grounded 3D Representation for Robotics. - Jad Abou-Chakra; Krishan Rana; Feras Dayoub; Niko Sünderhauf (CoRL, 2024)

Human-in-the-Loop Segmentation of Multi-species Coral Imagery. - Scarlett Raine; Ross Marchant; Brano Kusy; Frédéric Maire; Niko Sünderhauf; Tobias Fischer 001 (CVPR Workshops, 2024)

Open-Set Recognition in the Age of Vision-Language Models. - Dimity Miller; Niko Sünderhauf; Alex Kenna; Keita Mason (ECCV (42), 2024)

RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation. - Sourav Garg; Krishan Rana; Mehdi Hosseinzadeh 003; Lachlan Mares; Niko Sünderhauf; Feras Dayoub; Ian D. Reid 001 (ICRA, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

ParticleNeRF: A Particle-Based Encoding for Online Neural Radiance Fields. - Jad Abou-Chakra; Feras Dayoub; Niko Sünderhauf (WACV, 2024)

Open-Vocabulary Part-Based Grasping. - Tjeard van Oort; Dimity Miller; Will N. Browne; Nicolas Marticorena; Jesse Haviland; Niko Sünderhauf (CoRR, 2024)

Physically Embodied Gaussian Splatting: A Realtime Correctable World Model for Robotics. - Jad Abou-Chakra; Krishan Rana; Feras Dayoub; Niko Sünderhauf (CoRR, 2024)

RMMI: Enhanced Obstacle Avoidance for Reactive Mobile Manipulation using an Implicit Neural Map. - Nicolas Marticorena; Tobias Fischer 001; Jesse Haviland; Niko Sünderhauf (CoRR, 2024)

Affordance-Centric Policy Learning: Sample Efficient and Generalisable Robot Policy Learning using Affordance-Centric Task Frames. - Krishan Rana; Jad Abou-Chakra; Sourav Garg; Robert Lee; Ian D. Reid 001; Niko Sünderhauf (CoRR, 2024)

Multi-Modal 3D Scene Graph Updater for Shared and Dynamic Environments. - Emilio Olivastri; Jonathan Francis; Alberto Pretto; Niko Sünderhauf; Krishan Rana (CoRR, 2024)

Reducing Label Dependency for Underwater Scene Understanding: A Survey of Datasets, Techniques and Applications. - Scarlett Raine; Frédéric Maire; Niko Sünderhauf; Tobias Fischer 001 (CoRR, 2024)

Multi-View Pose-Agnostic Change Localization with Zero Labels. - Chamuditha Jayanga Galappaththige; Jason Lai; Lloyd Windrim; Donald G. Dansereau; Niko Sünderhauf; Dimity Miller (CVPR, 2025)

IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation. - Krishan Rana; Robert Lee; David Pershouse; Niko Sünderhauf (CoRR, 2025)