activity
20162026
most citedRobust Adversarial Reinforcement Learning

384 citations · 807 across the 37 of their papers we have counts for

collaborators
Showing 2022 · cs.ROShow all

8 papers · 2 filters

cs.RO2022★ 2 cited

Holo-Dex: Teaching Dexterity with Immersive Mixed Reality

Sridhar Pandian Arunachalam, Irmak Güzey, Soumith Chintala +1

A fundamental challenge in teaching robots is to provide an effective interface for human teachers to demonstrate useful skills to a robot. This challenge is exacerbated in dextero…

cs.RO2022★ 1 cited

That Sounds Right: Auditory Self-Supervision for Dynamic Robot Manipulation

Abitha Thankaraj, Lerrel Pinto

Learning to produce contact-rich, dynamic behaviors from raw sensory data has been a longstanding challenge in robotics. Prominent approaches primarily focus on using visual or tac…

cs.RO2022★ 6 cited

From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data

Zichen Jeff Cui, Yibin Wang, Nur Muhammad Mahi Shafiullah +1

While large-scale sequence modeling from offline data has led to impressive performance gains in natural language and image generation, directly translating such ideas to robotics…

cs.RO2022★ 70 cited

CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory

Nur Muhammad Mahi Shafiullah, Chris Paxton, Lerrel Pinto +2

We propose CLIP-Fields, an implicit scene model that can be used for a variety of tasks, such as segmentation, instance identification, semantic search over space, and view localiz…

cs.RO2022★ 8 cited

Watch and Match: Supercharging Imitation with Regularized Optimal Transport

Siddhant Haldar, Vaibhav Mathur, Denis Yarats +1

Imitation learning holds tremendous promise in learning policies efficiently for complex decision making problems. Current state-of-the-art algorithms often use inverse reinforceme…

cs.RO2022★ 5 cited

Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation

Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans +1

Optimizing behaviors for dexterous manipulation has been a longstanding challenge in robotics, with a variety of methods from model-based control to model-free reinforcement learni…