43 citations · 137 across the 15 of their papers we have counts for
21 papers
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
Allen Z. Ren, Anushri Dixit, Alexandra Bodrova +11
Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remai…
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning
David Brandfonbrener, Stephen Tu, Avi Singh +4
We consider how to most efficiently leverage teleoperator time to collect data for learning robust image-based value functions and policies for sparse reward robotic tasks. To acco…
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski +14
Despite decades of research, existing navigation systems still face real-world challenges when deployed in the wild, e.g., in cluttered home environments or in human-occupied publi…
Multiple View Performers for Shape Completion
David Watkins, Peter Allen, Krzysztof Choromanski +2
We propose the Multiple View Performer (MVP) - a new architecture for 3D shape completion from a series of temporally sequential views. MVP accomplishes this task by using linear-a…
Multiscale Sensor Fusion and Continuous Control with Neural CDEs
Sumeet Singh, Francis McCann Ramirez, Jacob Varley +2
Though robot learning is often formulated in terms of discrete-time Markov decision processes (MDPs), physical robots require near-continuous multiscale feedback control. Machines…
Implicit Kinematic Policies: Unifying Joint and Cartesian Action Spaces in End-to-End Robot Learning
Aditya Ganapathi, Pete Florence, Jake Varley +3
Action representation is an important yet often overlooked aspect in end-to-end robot learning with deep networks. Choosing one action space over another (e.g. target joint positio…