8 citations · 18 across the 6 of their papers we have counts for
6 papers
DexterityGen: Foundation Controller for Unprecedented Dexterity
Zhao-Heng Yin, Changhao Wang, Luis Pineda +11
Teaching robots dexterous manipulation skills, such as tool use, presents a significant challenge. Current approaches can be broadly categorized into two strategies: human teleoper…
From Simple to Complex Skills: The Case of In-Hand Object Reorientation
Haozhi Qi, Brent Yi, Mike Lambeta +3
Learning policies in simulation and transferring them to the real world has become a promising approach in dexterous manipulation. However, bridging the sim-to-real gap for each ne…
Digitizing Touch with an Artificial Multimodal Fingertip
Mike Lambeta, Tingfan Wu, Ali Sengul +20
Touch is a crucial sensing modality that provides rich information about object properties and interactions with the physical environment. Humans and robots both benefit from using…
Sparsh: Self-supervised touch representations for vision-based tactile sensing
Carolina Higuera, Akash Sharma, Chaithanya Krishna Bodduluri +8
In this work, we introduce general purpose touch representations for the increasingly accessible class of vision-based tactile sensors. Such sensors have led to many recent advance…
A Touch, Vision, and Language Dataset for Multimodal Alignment
Letian Fu, Gaurav Datta, Huang Huang +7
Touch is an important sensing modality for humans, but it has not yet been incorporated into a multimodal generative language model. This is partially due to the difficulty of obta…
General In-Hand Object Rotation with Vision and Touch
Haozhi Qi, Brent Yi, Sudharshan Suresh +4
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…