103 citations · 169 across the 20 of their papers we have counts for
10 papers · 1 filter
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…
P3-PO: Prescriptive Point Priors for Visuo-Spatial Generalization of Robot Policies
Mara Levy, Siddhant Haldar, Lerrel Pinto +1
Developing generalizable robot policies that can robustly handle varied environmental conditions and object instances remains a fundamental challenge in robot learning. While consi…
DynaMem: Online Dynamic Spatio-Semantic Memory for Open World Mobile Manipulation
Peiqi Liu, Zhanqiu Guo, Mohit Warke +4
Significant progress has been made in open-vocabulary mobile manipulation, where the goal is for a robot to perform tasks in any environment given a natural language description. H…
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning
Gaoyue Zhou, Hengkai Pan, Yann LeCun +1
The ability to predict future outcomes given control actions is fundamental for physical reasoning. However, such predictive models, often called world models, remains challenging…
DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control
Zichen Jeff Cui, Hengkai Pan, Aadhithya Iyer +2
Imitation learning has proven to be a powerful tool for training complex visuomotor policies. However, current methods often require hundreds to thousands of expert demonstrations…
Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments
Haritheja Etukuru, Norihito Naka, Zijin Hu +7
Robot models, particularly those trained with large amounts of data, have recently shown a plethora of real-world manipulation and navigation capabilities. Several independent effo…
BAKU: An Efficient Transformer for Multi-Task Policy Learning
Siddhant Haldar, Zhuoran Peng, Lerrel Pinto
Training generalist agents capable of solving diverse tasks is challenging, often requiring large datasets of expert demonstrations. This is particularly problematic in robotics, w…
OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation
Aadhithya Iyer, Zhuoran Peng, Yinlong Dai +4
Open-sourced, user-friendly tools form the bedrock of scientific advancement across disciplines. The widespread adoption of data-driven learning has led to remarkable progress in m…
Behavior Generation with Latent Actions
Seungjae Lee, Yibin Wang, Haritheja Etukuru +3
Generative modeling of complex behaviors from labeled datasets has been a longstanding problem in decision making. Unlike language or image generation, decision making requires mod…
OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics
Peiqi Liu, Yaswanth Orru, Jay Vakil +3
Remarkable progress has been made in recent years in the fields of vision, language, and robotics. We now have vision models capable of recognizing objects based on language querie…