News
Nov 2022
I attended the National PhD-AI Fall School, discussing topics such as Federated Learning, Domain Adaptation, and Kernel Methods by Prof. Lorenzo Rosasco.
Sep 2022 Our paper "Online vs. Offline Adaptive Domain Randomization Benchmark" will be published in the Springer Proceedings in Advanced Robotics 2022.
Jul 2022 I attended the International Computer Vision Summer School (ICVSS 2022) and won the Reading Group Competition led by Prof. Stefano Soatto.
Sep 2022 Our paper "Online vs. Offline Adaptive Domain Randomization Benchmark" will be published in the Springer Proceedings in Advanced Robotics 2022.
Jul 2022 I attended the International Computer Vision Summer School (ICVSS 2022) and won the Reading Group Competition led by Prof. Stefano Soatto.
About
Hi there! My name is Gabriele. I'm enrolled in the National PhD AI programme at Politecnico di Torino, complemented by the Ellis PhD&Post-Doc programme, and supervised by Prof. Tatiana Tommasi.
My areas of interest include reinforcement learning (RL), computer vision and robotics. Recently, I've been working on transferring RL robot policies from simulation to the real world.
The main goal of my research is to allow next-generation robots to be trained safely and efficiently through learning-based algorithms.
Publications
PaintNet: 3D Learning of Pose Paths Generators for Robotic Spray Painting
Gabriele Tiboni, Raffaello Camoriano, Tatiana Tommasi
Preprint, 2022
Paper/
Code/
Website
Online vs. Offline Adaptive Domain Randomization Benchmark
Gabriele Tiboni, Karol Arndt, Giuseppe Averta, Ville Kyrki, Tatiana Tommasi
Springer Proceedings in Advanced Robotics (SPAR), 2022
Paper/
Code
DROPO: Sim-to-Real Transfer with Offline Domain Randomization
Gabriele Tiboni, Karol Arndt, Ville Kyrki
Preprint, 2022
Paper/
Code
Towards Safe and Efficient Transfer of Robot Policies from Simulation to Real World
Gabriele Tiboni, Karol Arndt, Ville Kyrki, Barbara Caputo
M.Sc. Thesis, 2021
Thesis