AT-VLA proposes adaptive tactile injection and a dual-stream tactile reaction mechanism to enhance VLA models for contact-rich robotic manipulation with real-time responses.
Sparsh: Self-supervised touch representations for vision- based tactile sensing
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.RO 4verdicts
UNVERDICTED 4roles
method 1polarities
use method 1representative citing papers
DreamTacVLA grounds VLA models in contact physics by aligning multi-scale vision-tactile inputs and predicting future tactile states, reaching up to 95% success on contact-rich tasks.
ViTacFormer learns a cross-modal visuo-tactile latent space with autoregressive tactile prediction and an easy-to-hard curriculum, then uses the representation for imitation learning that yields ~50% higher success and the first reported 11-stage, 2.5-minute autonomous dexterous tasks.
Polyurethane vision-based tactile sensors are more resilient to normal loading, shear, and abrasion than silicone ones, extending the usable force range at the cost of low-force sensitivity.
citing papers explorer
-
AT-VLA: Adaptive Tactile Injection for Enhanced Feedback Reaction in Vision-Language-Action Models
AT-VLA proposes adaptive tactile injection and a dual-stream tactile reaction mechanism to enhance VLA models for contact-rich robotic manipulation with real-time responses.
-
Learning to Feel the Future: DreamTacVLA for Contact-Rich Manipulation
DreamTacVLA grounds VLA models in contact physics by aligning multi-scale vision-tactile inputs and predicting future tactile states, reaching up to 95% success on contact-rich tasks.
-
ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation
ViTacFormer learns a cross-modal visuo-tactile latent space with autoregressive tactile prediction and an easy-to-hard curriculum, then uses the representation for imitation learning that yields ~50% higher success and the first reported 11-stage, 2.5-minute autonomous dexterous tasks.
-
Characterizing the Resilience and Sensitivity of Polyurethane Vision-Based Tactile Sensors
Polyurethane vision-based tactile sensors are more resilient to normal loading, shear, and abrasion than silicone ones, extending the usable force range at the cost of low-force sensitivity.