Biography
Daniele joins ORI in May 2018 as a PostDoc Research Assistant under the suprvision on Prof. Paul Newman.
He did his PhD at the Univerista’ degli Studi di Pavia, in Italy, working on energy managements of power loads applied to robotics actuation.
He’s interested in cyber-physical systems, in particular robotics, and artificial intelligence.
Recent Publications
Visuo-tactile recognition of partial point clouds using PointNet and curriculum learning
Parsons C, Albini A, De 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},
author={Parsons C, Albini A, De 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(1), 16939
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},
pages={16939},
publisher={Springer Science and Business Media LLC},
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
BibTeX
@inproceedings{depthsimssemipa-2022/7,
title={Depth-SIMS: semi-parametric image and depth synthesis},
author={Musat V, De Martini D, Gadd M & Newman P},
booktitle={ International Conference on Robotics and Automation (ICRA 2022)},
pages={2388-2394},
year = "2022"
}
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
BibTeX
@article{whatgoesaroundl-2022/6,
title={What goes around: leveraging a constant-curvature motion constraint in radar odometry},
author={Aldera R, Gadd M, De Martini D & Newman P},
journal={IEEE Robotics and Automation Letters},
volume={7},
pages={7865-7872},
publisher={IEEE},
year = "2022"
}
The Oxford Road Boundaries Dataset
Suleymanov T, Gadd M, De Martini D & Newman P (2022)
BibTeX
@inproceedings{theoxfordroadbo-2022/1,
title={The Oxford Road Boundaries Dataset},
author={Suleymanov T, Gadd M, De Martini D & Newman P},
booktitle={32nd IEEE Intelligent Vehicles Symposium (IV21) -- Workshop on 3D-Deep Learning for Automated Driving (3D-DLAD)},
year = "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
BibTeX
@inproceedings{contrastivelear-2022/1,
title={Contrastive learning for unsupervised radar place recognition},
author={Gadd M, De Martini D & Newman P},
booktitle={20th International Conference on Advanced Robotics (ICAR 2021)},
pages={344-349},
year = "2022"
}
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"
}
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
BibTeX
@inproceedings{foolmeoncerobus-2021/10,
title={Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning},
author={Williams D, Gadd M, De Martini D & Newman P},
booktitle={ICRA 2021},
pages={9536-9542},
year = "2021"
}
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"
}
