Gianmarco Roggiolani

Ph.D. student
Contact:
Email: gianmarco.roggiolani@nulligg.uni-bonn.de
Tel: +49 – 228 – 73 – 29 05
Fax: +49 – 228 – 73 – 27 12
Office: Nussallee 15, 1. OG, room 1.003
Address:
University of Bonn
Photogrammetry, IGG
Nussallee 15
53115 Bonn

LinkedIn

Research Interests

  • Computer Vision
  • Self-Supervised Learning
  • SLAM
  • Agricultural Robotics

Short CV

Gianmarco Roggiolani is a PhD student at the University of Bonn. He received a Bachelor’s degree in Computer and Automatic Engineering (2018) and a Master’s degree in Artificial Intelligence and Robotics (2021) from La Sapienza University in Rome, Italy. His thesis was focused on the integration of the IMU sensor into a SLAM pipeline.

Projects

  • PhenoRob – Robotics and Phenotyping for Sustainable Crop Production (DFG Cluster of Excellence)

Teaching

  • Sensors and State Estimation – Winter Semester 2021
  • Advanced Techniques for Sensors and State Estimation – Summer Semester 2022
  • Master Project “Self-Supervised Contrastive Learning in Traffic Scenes” – Winter Semester 2022

Publications

2023

  • G. Roggiolani, M. Sodano, F. Magistri, T. Guadagnino, J. Behley, and C. Stachniss, “Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural Domain,” in Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2023.
    [BibTeX] [PDF] [Code] [Video] 
    @inproceedings{roggiolani2023icra-hajs,
author = {G. Roggiolani and M. Sodano and F. Magistri and T. Guadagnino and J. Behley and C. Stachniss},
title = {{Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural Domain}},
booktitle = icra,
year = {2023},
codeurl = {https://github.com/PRBonn/HAPT},
videourl = {https://youtu.be/miuOJjxlJic}
}
  • G. Roggiolani, F. Magistri, T. Guadagnino, J. Weyler, G. Grisetti, C. Stachniss, and J. Behley, “On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics,” in Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2023.
    [BibTeX] [PDF] [Code] [Video] 
    @inproceedings{roggiolani2023icra-odsp,
author = {G. Roggiolani and F. Magistri and T. Guadagnino and J. Weyler and G. Grisetti and C. Stachniss and J. Behley},
title = {{On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics}},
booktitle = icra,
year = 2023,
codeurl= {https://github.com/PRBonn/agri-pretraining},
videourl = {https://youtu.be/FDWY_UnfsBs}
}