164 citations · 170 across the 8 of their papers we have counts for
9 papers
Ego-Exo4D Human Meshes Dataset: 4D Human Motion Reconstruction for Ego-Exo Captures
Abhiram Maddukuri, Georgios Pavlakos
Ego-Exo4D is a large-scale dataset providing synchronized egocentric and multi-view exocentric video, a rich resource for skill learning and assessment, procedural activity underst…
A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies
Yu Lei, Minghuan Liu, Abhiram Maddukuri +2
Co-training, which combines limited in-domain real-world data with abundant surrogate data such as simulation or cross-embodiment robot data, is widely used for training generative…
RoboCasa365: A Large-Scale Simulation Framework for Training and Benchmarking Generalist Robots
Soroush Nasiriany, Sepehr Nasiriany, Abhiram Maddukuri +1
Recent advances in robot learning have accelerated progress toward generalist robots that can perform everyday tasks in human environments. Yet it remains difficult to gauge how cl…
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…
Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation
Abhiram Maddukuri, Zhenyu Jiang, Lawrence Yunliang Chen +12
Large real-world robot datasets hold great potential to train generalist robot models, but scaling real-world human data collection is time-consuming and resource-intensive. Simula…
Reinforcement Learning for Dynamic Memory Allocation
Arisrei Lim, Abhiram Maddukuri
In recent years, reinforcement learning (RL) has gained popularity and has been applied to a wide range of tasks. One such popular domain where RL has been effective is resource ma…
RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Soroush Nasiriany, Abhiram Maddukuri, Lance Zhang +5
Recent advancements in Artificial Intelligence (AI) have largely been propelled by scaling. In Robotics, scaling is hindered by the lack of access to massive robot datasets. We adv…
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair +98
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar +6
robosuite is a simulation framework for robot learning powered by the MuJoCo physics engine. It offers a modular design for creating robotic tasks as well as a suite of benchmark e…