9 papers · 1 filter
Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models
Haoran Hao, Shahram Najam Syed, Jeff Schneider +1
While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performance can degrade when adapted to…
FAR: Failure-Aware Retry for Test-Time Recovery and Continual Policy Improvement
Haoran Hao, Shahram Najam Syed, Jeffrey Ichnowski +1
Robot policies inevitably encounter failures when deployed in real environments. Naive retries often repeat the same mistakes, while many existing recovery methods rely on human in…
3PoinTr: 3D Point Tracks for Learning Manipulation from Unconstrained Human Videos
Adam Hung, Bardienus Pieter Duisterhof, Jeffrey Ichnowski
Learning manipulation policies from human videos could greatly reduce the need for expensive robot demonstrations, but existing approaches typically require restrictive assumptions…
Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation
Shahram Najam Syed, Arthur Jakobsson, Haoran Hao +1
Vision-Language-Action (VLA) models generalize across static manipulation but fail when objects move during task execution. They map the current observation to an action and assume…
Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation
Arthur Jakobsson, Abhinav Mahajan, Karthik Pullalarevu +6
Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. To mitigate this, we present a novel approach that…
Functional Force-Aware Retargeting from Virtual Human Demos to Soft Robot Policies
Uksang Yoo, Mengjia Zhu, Evan Pezent +8
We introduce SoftAct, a framework for teaching soft robot hands to perform human-like manipulation skills by explicitly reasoning about contact forces. Leveraging immersive virtual…