activity
20202025
most citedOpen X-Embodiment: Robotic Learning Datasets and RT-X Models

103 citations · 114 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2025★ 1 cited

Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169

General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…

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★ 8 cited

ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation

ALOHA 2 Team, Jorge Aldaco, Travis Armstrong +23

Diverse demonstration datasets have powered significant advances in robot learning, but the dexterity and scale of such data can be limited by the hardware cost, the hardware robus…

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…

cs.RO2023★ 2 cited

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators

Alexander Herzog, Kanishka Rao, Karol Hausman +37

We describe a system for deep reinforcement learning of robotic manipulation skills applied to a large-scale real-world task: sorting recyclables and trash in office buildings. Rea…

cs.RO2020

Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data

Mohi Khansari, Daniel Kappler, Jianlan Luo +2

This paper introduces Action Image, a new grasp proposal representation that allows learning an end-to-end deep-grasping policy. Our model achieves grasp success on re…