Showing 50 publications by Daniele De Martini
AutoInspect: towards long-term autonomous inspection and monitoring
Staniaszek M, Flatscher T, Rowell J, Niu H, Liu W et al. (2025), IEEE Transactions on Field Robotics
The Oxford RobotCycle Project: A Multimodal Urban Cycling Dataset for Assessing the Safety of Vulnerable Road Users
Panagiotaki E, Thuremella D, Baghabrah J, Sze S, Fu LFT et al. (2025), IEEE Transactions on Field Robotics, PP(99), 1-1
BibTeX
@article{theoxfordrobotc-2025/5,
title={The Oxford RobotCycle Project: A Multimodal Urban Cycling Dataset for Assessing the Safety of Vulnerable Road Users},
author={Panagiotaki E, Thuremella D, Baghabrah J, Sze S, Fu LFT et al.},
journal={IEEE Transactions on Field Robotics},
volume={PP},
pages={1-1},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2025"
}
Bayesian Radar Cosplace: Directly estimating location uncertainty in radar place recognition
Agarwal S, Yuan J, Newman P, De Martini D & Gadd M (2025), IET Radar Sonar & Navigation, 19(1)
BibTeX
@article{bayesianradarco-2025/3,
title={Bayesian Radar Cosplace: Directly estimating location uncertainty in radar place recognition},
author={Agarwal S, Yuan J, Newman P, De Martini D & Gadd M},
journal={IET Radar Sonar & Navigation},
volume={19},
publisher={Institution of Engineering and Technology (IET)},
year = "2025"
}
Tiny Lidars for Manipulator Self-Awareness: Sensor Characterization and Initial Localization Experiments
Caroleo G, Albini A, De Martini D, Barfoot TD & Maiolino P (2025)
BibTeX
@inproceedings{tinylidarsforma-2025/3,
title={Tiny Lidars for Manipulator Self-Awareness: Sensor Characterization and Initial Localization Experiments},
author={Caroleo G, Albini A, De Martini D, Barfoot TD & Maiolino P},
booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = "2025"
}
NeuralFloors++: consistent street-level scene generation from BEV semantic maps
Musat V, De Martini D, Gadd M & Newman P (2024), 12872-12879
BibTeX
@inproceedings{neuralfloorscon-2024/12,
title={NeuralFloors++: consistent street-level scene generation from BEV semantic maps},
author={Musat V, De Martini D, Gadd M & Newman P},
booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)},
pages={12872-12879},
year = "2024"
}
GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation
Panagiotaki E, Pramatarov G, Kunze L & Martini DD (2024)
BibTeX
@inproceedings{graphsceneondem-2024/10,
title={GraphSCENE: On-Demand Critical Scenario Generation for Autonomous
Vehicles in Simulation},
author={Panagiotaki E, Pramatarov G, Kunze L & Martini DD},
booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = "2024"
}
NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
Panagiotaki E, De Martini D, Kunze L & Veličković P (2024)
BibTeX
@misc{naricpneuralexe-2024/10,
title={NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms},
author={Panagiotaki E, De Martini D, Kunze L & Veličković P},
year = "2024"
}
Robot-relay:building-wide, calibration-less visual servoing with learned sensor handover networks
Robinson L, Gadd M, Newman P & De Martini D (2024), Experimental Robotics: The 18th International Symposium, 129-140
BibTeX
@inproceedings{robotrelaybuild-2024/8,
title={Robot-relay:building-wide, calibration-less visual servoing with learned sensor handover networks},
author={Robinson L, Gadd M, Newman P & De Martini D},
booktitle={18th International Symposium on Experimental Robotics (ISER 2023)},
pages={129-140},
year = "2024"
}
VDNA-PR: using general dataset representations for robust sequential visual place recognition
Ramtoula B, De Martini D, Gadd M & Newman P (2024), 2024 IEEE International Conference on Robotics and Automation (ICRA), 15883-15889
BibTeX
@inproceedings{vdnaprusinggene-2024/8,
title={VDNA-PR: using general dataset representations for robust sequential visual place recognition},
author={Ramtoula B, De Martini D, Gadd M & Newman P},
booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA 2024)},
pages={15883-15889},
year = "2024"
}
What you see is what you get: experience ranking with deep neural dataset-to-dataset similarity for topological localisation
Gadd M, Ramtoula B, De Martini D & Newman P (2024), Experimental Robotics: The 18th International Symposium, 595-607
BibTeX
@inproceedings{whatyouseeiswha-2024/8,
title={What you see is what you get: experience ranking with deep neural dataset-to-dataset similarity for topological localisation},
author={Gadd M, Ramtoula B, De Martini D & Newman P},
booktitle={18th International Symposium on Experimental Robotics (ISER 2023)},
pages={595-607},
year = "2024"
}
That's my point: compact object-centric LiDAR pose estimation for large-scale outdoor localisation
Pramatarov G, Gadd M, Newman P & De Martini D (2024), 2024 IEEE International Conference on Robotics and Automation (ICRA), 12276-12282
BibTeX
@inproceedings{thatsmypointcom-2024/8,
title={That's my point: compact object-centric LiDAR pose estimation for large-scale outdoor localisation},
author={Pramatarov G, Gadd M, Newman P & De Martini D},
booktitle={ 2024 IEEE International Conference on Robotics and Automation (ICRA 2024)},
pages={12276-12282},
year = "2024"
}
Masked γ-SSL: learning uncertainty estimation via masked image modeling
Williams DSW, Gadd M, Newman P & De Martini D (2024), 2024 IEEE International Conference on Robotics and Automation (ICRA), 16192-16198
BibTeX
@inproceedings{maskedssllearni-2024/8,
title={Masked γ-SSL: learning uncertainty estimation via masked image modeling},
author={Williams DSW, Gadd M, Newman P & De Martini D},
booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA 2024)},
pages={16192-16198},
year = "2024"
}
RobotCycle: Assessing Cycling Safety in Urban Environments
Panagiotaki E, Reinmund T, Mouton S, Pitt L, Shanthini AS et al. (2024)
Watching grass grow: long-term visual navigation and mission planning for autonomous biodiversity monitoring
Gadd M, De Martini D, Pitt L, Tubby W, Towlson M et al. (2024)
BibTeX
@misc{watchinggrassgr-2024/5,
title={Watching grass grow: long-term visual navigation and mission planning for autonomous biodiversity monitoring},
author={Gadd M, De Martini D, Pitt L, Tubby W, Towlson M et al.},
year = "2024"
}
TAGIC: Task-Guided Image Communication Framework for Seamless Teleoperation
Diao Y, Zhang Y, Zhao PG & De Martini D (2024), 00, 1-2
BibTeX
@inproceedings{tagictaskguided-2024/5,
title={TAGIC: Task-Guided Image Communication Framework for Seamless Teleoperation},
author={Diao Y, Zhang Y, Zhao PG & De Martini D},
booktitle={IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},
pages={1-2},
year = "2024"
}
Mitigating distributional shift in semantic segmentation via uncertainty estimation from unlabeled data
Williams DSW, De Martini D, Gadd M & Newman P (2024), IEEE Transactions on Robotics, 40, 3146-3165
BibTeX
@article{mitigatingdistr-2024/5,
title={Mitigating distributional shift in semantic segmentation via uncertainty estimation from unlabeled data},
author={Williams DSW, De Martini D, Gadd M & Newman P},
journal={IEEE Transactions on Robotics},
volume={40},
pages={3146-3165},
publisher={IEEE},
year = "2024"
}
Real-time cyber/physical interplay in scheduling for peak load optimization in cyber-physical energy systems
De Martini D, Benetti G & Facchinetti T (2024), Intelligent Systems with Applications, 22
BibTeX
@article{realtimecyberph-2024/4,
title={Real-time cyber/physical interplay in scheduling for peak load optimization in cyber-physical energy systems},
author={De Martini D, Benetti G & Facchinetti T},
journal={Intelligent Systems with Applications},
volume={22},
number={200380},
publisher={Elsevier},
year = "2024"
}
Doppler-aware odometry from FMCW scanning radar
Rennie F, Williams D, Newman P & De Martini D (2024), 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 5126-5132
Semantic interpretation and validation of graph attention-based explanations for GNN models
Panagiotaki E, De Martini D & Kunze L (2024)
SEM-GAT: explainable semantic pose estimation using learned graph attention
Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L (2024), 367-374
BibTeX
@inproceedings{semgatexplainab-2024/2,
title={SEM-GAT: explainable semantic pose estimation using learned graph attention},
author={Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L},
booktitle={21st International Conference on Advanced Robotics (ICAR 2023)},
pages={367-374},
year = "2024"
}
OORD: The Oxford Offroad Radar Dataset
Gadd M, De Martini D, Bartlett O, Murcutt P, Towlson M et al. (2024), IEEE Transactions on Intelligent Transportation Systems, 25(11), 18779-18790
Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control
Robinson L, De Martini D, Gadd M & Newman P (2023), 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6364-6370
BibTeX
@inproceedings{visualservoingo-2023/12,
title={Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control},
author={Robinson L, De Martini D, Gadd M & Newman P},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)},
pages={6364-6370},
year = "2023"
}
Self-supervised Lidar place recognition in overhead imagery using unpaired data
Tang TY, De Martini D & Newman PM (2023), Proceedings of Robotics: Science and Systems 2023
Visual DNA: representing and comparing images using distributions of neuron activations
Ramtoula B, Gadd M, Newman P & De Martini D (2023), 11113-11123
BibTeX
@inproceedings{visualdnarepres-2023/8,
title={Visual DNA: representing and comparing images using distributions of neuron activations},
author={Ramtoula B, Gadd M, Newman P & De Martini D},
booktitle={IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2023)},
pages={11113-11123},
year = "2023"
}
Explainable action prediction through self-supervision on scene graphs
Kochakarn P, De Martini D, Omeiza D & Kunze L (2023), Proceedings of the International Conference on Robotics and Automation (ICRA 2023), 1479-1485
Roll-Drop: accounting for observation noise with a single parameter
Campanaro L, De Martini D, Gangapurwala S, Merkt W & Havoutis I (2023), Proceedings of The 5th Annual Learning for Dynamics and Control Conference, 718-730
BibTeX
@inproceedings{rolldropaccount-2023/6,
title={Roll-Drop: accounting for observation noise with a single parameter},
author={Campanaro L, De Martini D, Gangapurwala S, Merkt W & Havoutis I},
booktitle={5th Annual Learning for Dynamics and Control Conference (L4DC 2023)},
pages={718-730},
year = "2023"
}
Point-based metric and topological localisation between lidar and overhead imagery
Tang TY, De Martini D & Newman P (2023), Autonomous Robots, 47(5), 595-615
Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse
Meng Z, She C, Zhao G & De Martini D (2023), IEEE Journal on Selected Areas in Communications, 41(1), 288-300
BibTeX
@article{samplingcommuni-2023/1,
title={Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse},
author={Meng Z, She C, Zhao G & De Martini D},
journal={IEEE Journal on Selected Areas in Communications},
volume={41},
pages={288-300},
year = "2023"
}
SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attention
Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L (2023), 2023 21ST INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS, ICAR, 367-374
BibTeX
@inproceedings{semgatexplainab-2023/,
title={SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attention},
author={Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L},
pages={367-374},
year = "2023"
}
Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models
Panagiotaki E, De Martini D & Kunze L (2023), 2023 21ST INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS, ICAR, 375-380
BibTeX
@inproceedings{semanticinterpr-2023/,
title={Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models},
author={Panagiotaki E, De Martini D & Kunze L},
pages={375-380},
year = "2023"
}
Visuo-tactile recognition of partial point clouds using PointNet and curriculum learning: enabling tactile perception from visual data
Parsons C, Albini A, Martini D & Maiolino P (2022), IEEE Robotics and Automation Magazine
BibTeX
@article{visuotactilerec-2022/10,
title={Visuo-tactile recognition of partial point clouds using PointNet and curriculum learning: enabling tactile perception from visual data},
author={Parsons C, Albini A, Martini D & Maiolino P},
journal={IEEE Robotics and Automation Magazine},
publisher={IEEE},
year = "2022"
}
RaVÆn: unsupervised change detection of extreme events using ML on-board satellites
Růžička V, Vaughan A, De Martini D, Fulton J, Salvatelli V et al. (2022), Scientific reports, 12
BibTeX
@article{ravnunsupervise-2022/10,
title={RaVÆn: unsupervised change detection of extreme events using ML on-board satellites},
author={Růžička V, Vaughan A, De Martini D, Fulton J, Salvatelli V et al.},
journal={Scientific reports},
volume={12},
number={16939},
publisher={Springer Nature},
year = "2022"
}
Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry
Weston R, Gadd M, De Martini D, Newman P & Posner H (2022), Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2022), 2186-2192
BibTeX
@inproceedings{fastmbymleverag-2022/7,
title={Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry},
author={Weston R, Gadd M, De Martini D, Newman P & Posner H},
booktitle={IEEE International Conference on Robotics and Automation (ICRA 2022)},
pages={2186-2192},
year = "2022"
}
Depth-SIMS: semi-parametric image and depth synthesis
Musat V, De Martini D, Gadd M & Newman P (2022), 2022 International Conference on Robotics and Automation (ICRA), 2388-2394
What goes around: leveraging a constant-curvature motion constraint in radar odometry
Aldera R, Gadd M, De Martini D & Newman P (2022), IEEE Robotics and Automation Letters, 7(3), 7865-7872
The Oxford Road Boundaries Dataset
Suleymanov T, Gadd M, De Martini D & Newman P (2022)
Contrastive learning for unsupervised radar place recognition
Gadd M, De Martini D & Newman P (2022), 2021 20th International Conference on Advanced Robotics (ICAR), 344-349
Unsupervised change detection of extreme events using ML on-board
Ruzicka V, Vaughan A, De Martini D, Fulton J, Salvatelli V et al. (2021)
BibTeX
@inproceedings{unsupervisedcha-2021/12,
title={Unsupervised change detection of extreme events using ML on-board},
author={Ruzicka V, Vaughan A, De Martini D, Fulton J, Salvatelli V et al.},
booktitle={NeurIPS Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop (AI+HADR), 2021},
year = "2021"
}
BoxGraph: semantic place recognition and pose estimation from 3D LiDAR
Pramatarov G, De Martini D, Gadd M & Newman P (2021), 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 7004-7011
BibTeX
@inproceedings{boxgraphsemanti-2021/12,
title={BoxGraph: semantic place recognition and pose estimation from 3D LiDAR},
author={Pramatarov G, De Martini D, Gadd M & Newman P},
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems},
pages={7004-7011},
year = "2021"
}
Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning
Williams D, Gadd M, De Martini D & Newman P (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA), 9536-9542
CPG-ACTOR: reinforcement learning for central pattern generators
Campanaro L, Gangapurwala S, De Martini D, Merkt W & Havoutis I (2021), Towards Autonomous Robotic Systems, 25-35
Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization
Tang TY, De Martini D, Wu S & Newman P (2021), The International Journal of Robotics Research, 40(12-14), 1488-1509
BibTeX
@article{selfsupervisedl-2021/9,
title={Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization},
author={Tang TY, De Martini D, Wu S & Newman P},
journal={The International Journal of Robotics Research},
volume={40},
pages={1488-1509},
publisher={SAGE Publications},
year = "2021"
}
Get to the point: learning lidar place recognition and metric localisation using overhead imagery
Tang TY, De Martini D & Newman P (2021), Proceedings of Robotics: Science and Systems, 2021
BibTeX
@article{gettothepointle-2021/7,
title={Get to the point: learning lidar place recognition and metric localisation using overhead imagery},
author={Tang TY, De Martini D & Newman P},
journal={Proceedings of Robotics: Science and Systems, 2021},
publisher={Robotics: Science and Systems},
year = "2021"
}
Unsupervised place recognition with deep embedding learning over radar videos
Gadd M, De Martini D & Newman P (2021)
BibTeX
@inproceedings{unsupervisedpla-2021/5,
title={Unsupervised place recognition with deep embedding learning over radar videos},
author={Gadd M, De Martini D & Newman P},
booktitle={2021 ICRA Workshop: Radar Perception for All-Weather Autonomy},
year = "2021"
}
RainBench: Towards global precipitation forecasting from satellite imagery
de Witt CS, Tong C, Zantedeschi V, De Martini D, Kalaitzis A et al. (2021), Thirty-fifth AAAI Conference on Artificial Intelligence, 35(17), 14902-14910
BibTeX
@inproceedings{rainbenchtoward-2021/5,
title={RainBench: Towards global precipitation forecasting from satellite imagery},
author={de Witt CS, Tong C, Zantedeschi V, De Martini D, Kalaitzis A et al.},
booktitle={35th AAAI Conference on Artificial Intelligence (AAAI 2021)},
pages={14902-14910},
year = "2021"
}
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
Williams D, Gadd M, De Martini D & Newman P (2021)
The hulk: design and development of a weather-proof vehicle for long-term autonomy in outdoor environments
Kyberd S, Attias J, Get P, Murcutt P, Prahacs C et al. (2021), International Conference on Field and Service Robotics (FSR), 16(2021), 101-114
RSS-Net: weakly-supervised multi-class semantic segmentation with FMCW radar
Kaul P, De Martini D, Gadd M & Newman P (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV2020)(2020), 431-436
Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios
Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV), 150-155
BibTeX
@inproceedings{senseassessexpl-2021/1,
title={Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios},
author={Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L},
booktitle={IEEE Intelligent Vehicles Symposium (IV), Workshop on Ensuring and Validating Safety for Automated Vehicles (EVSAV)},
pages={150-155},
year = "2021"
}