5 papers · 1 filter
Whole-Body Dexterity
Conor Mc Gartoll, An Dang, Pranay Thangeda +5
Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the entire body by bracing and slidi…
HULK: Learning Whole-Body Forceful Loco-Manipulation for Humanoids
An Dang, Arturo Flores Alvarez, Yu-Ming Chen +5
Humanoid loco-manipulation of large, heavy objects demands forceful interaction across the entire body. However, such payloads shift a humanoid's center of mass and impose sustaine…
HydroShear: Hydroelastic Shear Simulation for Tactile Sim-to-Real Reinforcement Learning
An Dang, Jayjun Lee, Mustafa Mukadam +4
In this paper, we address the problem of tactile sim-to-real policy transfer for contact-rich tasks. Existing methods primarily focus on vision-based sensors and emphasize image re…
Hydrosoft: Non-Holonomic Hydroelastic Models for Compliant Tactile Manipulation
Miquel Oller, An Dang, Nima Fazeli
Tactile sensors have long been valued for their perceptual capabilities, offering rich insights into the otherwise hidden interface between the robot and grasped objects. Yet their…
Bimanual In-hand Manipulation using Dual Limit Surfaces
An Dang, James Lorenz, Xili Yi +1
In-hand object manipulation is an important capability for dexterous manipulation. In this paper, we introduce a modeling and planning framework for in-hand object reconfiguration,…