9 papers · 1 filter
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation
Wei-Cheng Tseng, Gashon Hussein, Yuzhu Dong +9
Evaluating generalist robot manipulation policies in the real world is expensive, slow, and difficult to scale. Action-conditioned video world models offer a scalable alternative b…
, But Make It Fly: Physics-Guided Transfer of VLA Models to Aerial Manipulation
Johnathan Tucker, Denis Liu, Aiden Swann +7
Vision-Language-Action (VLA) models such as have demonstrated remarkable generalization across diverse fixed-base manipulators. However, transferring these foundation models…
MEM: Multi-Scale Embodied Memory for Vision Language Action Models
Marcel Torne, Karl Pertsch, Homer Walke +14
Conventionally, memory in end-to-end robotic learning involves inputting a sequence of past observations into the learned policy. However, in complex multi-stage real-world tasks,…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
Michael Ahn, Debidatta Dwibedi, Chelsea Finn +24
Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data to reason about useful tasks. However,…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…