activity
20232026
most citedOpen X-Embodiment: Robotic Learning Datasets and RT-X Models

103 citations · 110 across the 5 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Hydra-0: Action Flow for Generalist World Modeling and Control

Hongyu Li, Bowen Wen, Xinghao Zhu +8

We introduce Hydra-0, a generalist world model conditioned on action flow, which represents robot actions as pixel motion. This shared visual interface enables generalist world mod…

cs.RO2025

Towards Embodiment Scaling Laws in Robot Locomotion

Bo Ai, Liu Dai, Nico Bohlinger +7

Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…

cs.RO2024

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning

Charles Xu, Qiyang Li, Jianlan Luo +1

Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…

cs.CV2024★ 1 cited

BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation

Yunhao Ge, Yihe Tang, Jiashu Xu +20

The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-wo…

cs.RO2024★ 6 cited

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation

Chengshu Li, Ruohan Zhang, Josiah Wong +32

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an extensive s…

cs.RO2023★ 103 cited

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…