General In-Hand Object Rotation with Vision and Touch
Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Beigetragen › Begutachtung
Beitragende
Abstract
We introduce RotateIt, a system that enables fingertip-based object rotation along multiple axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it has access to ground-truth object shapes and physical properties. Then we distill it to operate on realistic yet noisy simulated visuotactile and proprioceptive sensory inputs. These multimodal inputs are fused via a visuotactile transformer, enabling online inference of object shapes and physical properties during deployment. We show significant performance improvements over prior methods and the importance of visual and tactile sensing.
Details
Originalsprache | Englisch |
---|---|
Fachzeitschrift | Proceedings of Machine Learning Research |
Jahrgang | 229 |
Publikationsstatus | Veröffentlicht - 2023 |
Peer-Review-Status | Ja |
Konferenz
Titel | 7th Conference on Robot Learning |
---|---|
Kurztitel | CoRL 2023 |
Veranstaltungsnummer | 7 |
Dauer | 6 - 9 November 2023 |
Webseite | |
Bekanntheitsgrad | Internationale Veranstaltung |
Ort | Starling Hotel |
Stadt | Atlanta |
Land | USA/Vereinigte Staaten |
Externe IDs
ORCID | /0000-0001-9430-8433/work/158768044 |
---|
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- In-Hand Object Rotation, Reinforcement Learning, Sim-to-Real, Tactile Sensing, Transformer, Visuotactile Manipulation