3 papers
cs.RO2026
Learning Equivariant Neural-Augmented Object Dynamics From Few Interactions
Sergio Orozco, Tushar Kusnur, Brandon May +2
Learning data-efficient object dynamics models for robotic manipulation remains challenging, especially for deformable objects. A popular approach is to model objects as sets of 3D…
cs.CV2026
Show, Don't Tell: Detecting Novel Objects by Watching Human Videos
James Akl, Jose Nicolas Avendano Arbelaez, James Barabas +16
How can a robot quickly identify and recognize new objects shown to it during a human demonstration? Existing closed-set object detectors frequently fail at this because the object…
cs.RO2026
EMPM: Embodied MPM for Modeling and Simulation of Deformable Objects
Yunuo Chen, Yafei Hu, Lingfeng Sun +3
Modeling deformable objects - especially continuum materials - in a way that is physically plausible, generalizable, and data-efficient remains challenging across 3D vision, graphi…