103 citations · 191 across the 17 of their papers we have counts for
18 papers
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…
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…
IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning
Ryan Hoque, Ajay Mandlekar, Caelan Garrett +2
Imitation learning is a promising paradigm for training robot control policies, but these policies can suffer from distribution shift, where the conditions at evaluation time diffe…
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…
FogROS2-SGC: A ROS2 Cloud Robotics Platform for Secure Global Connectivity
Kaiyuan Chen, Ryan Hoque, Karthik Dharmarajan +5
The Robot Operating System (ROS2) is the most widely used software platform for building robotics applications. FogROS2 extends ROS2 to allow robots to access cloud computing on de…
IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors
Gaurav Datta, Ryan Hoque, Anrui Gu +2
Imitation learning has been applied to a range of robotic tasks, but can struggle when robots encounter edge cases that are not represented in the training data (i.e., distribution…