8 citations · 19 across the 11 of their papers we have counts for
13 papers
Rho: A Foundation for Efficiently Adaptable VLA Models
Rho Team, Simran Bagaria, Daphne Chen +11
General-purpose physical AI models must combine broad visual and linguistic capabilities with precise control across robot embodiments and efficient adaptation to downstream tasks.…
FlowDAgger: Human-in-the-Loop Adaptation of Generative Robot Policies in Latent Space
Michael Murray, Daphne Chen, Simran Bagaria +7
Pretrained generative robot policies based on flow matching and diffusion have achieved impressive results across a wide range of manipulation tasks. Yet real-world deployments rou…
TactAlign: Human-to-Robot Policy Transfer via Tactile Alignment
Youngsun Wi, Jessica Yin, Elvis Xiang +5
Human demonstrations collected by wearable devices (e.g., tactile gloves) provide fast and dexterous supervision for policy learning, and are guided by rich, natural tactile feedba…
Benchmarking Affordance Generalization with BusyBox
Dean Fortier, Timothy Adamson, Tess Hellebrekers +5
Vision-Language-Action (VLA) models have been attracting the attention of researchers and practitioners thanks to their promise of generalization. Although single-task policies sti…
OSMO: Open-Source Tactile Glove for Human-to-Robot Skill Transfer
Jessica Yin, Haozhi Qi, Youngsun Wi +7
Human video demonstrations provide abundant training data for learning robot policies, but video alone cannot capture the rich contact signals critical for mastering manipulation.…
Self-supervised perception for tactile skin covered dexterous hands
Akash Sharma, Carolina Higuera, Chaithanya Krishna Bodduluri +9
We present Sparsh-skin, a pre-trained encoder for magnetic skin sensors distributed across the fingertips, phalanges, and palm of a dexterous robot hand. Magnetic tactile skins off…
AnySkin: Plug-and-play Skin Sensing for Robotic Touch
Raunaq Bhirangi, Venkatesh Pattabiraman, Enes Erciyes +3
While tactile sensing is widely accepted as an important and useful sensing modality, its use pales in comparison to other sensory modalities like vision and proprioception. AnySki…
Learning In-Hand Translation Using Tactile Skin With Shear and Normal Force Sensing
Jessica Yin, Haozhi Qi, Jitendra Malik +3
Recent progress in reinforcement learning (RL) and tactile sensing has significantly advanced dexterous manipulation. However, these methods often utilize simplified tactile signal…
Hearing Touch: Audio-Visual Pretraining for Contact-Rich Manipulation
Jared Mejia, Victoria Dean, Tess Hellebrekers +1
Although pre-training on a large amount of data is beneficial for robot learning, current paradigms only perform large-scale pretraining for visual representations, whereas represe…
Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling
Raunaq Bhirangi, Chenyu Wang, Venkatesh Pattabiraman +4
Reasoning from sequences of raw sensory data is a ubiquitous problem across fields ranging from medical devices to robotics. These problems often involve using long sequences of ra…
All the Feels: A dexterous hand with large-area tactile sensing
Raunaq Bhirangi, Abigail DeFranco, Jacob Adkins +4
High cost and lack of reliability has precluded the widespread adoption of dexterous hands in robotics. Furthermore, the lack of a viable tactile sensor capable of sensing over the…
Linear Delta Arrays for Compliant Dexterous Distributed Manipulation
Sarvesh Patil, Tony Tao, Tess Hellebrekers +2
This paper presents a new type of distributed dexterous manipulator: delta arrays. Our delta array setup consists of 64 linearly-actuated delta robots with 3D-printed compliant lin…
ReSkin: versatile, replaceable, lasting tactile skins
Raunaq Bhirangi, Tess Hellebrekers, Carmel Majidi +1
Soft sensors have continued growing interest in robotics, due to their ability to enable both passive conformal contact from the material properties and active contact data from th…