activity
20212024
most citedGenerative Expressive Robot Behaviors using Large Language Models

52 citations · 159 across the 22 of their papers we have counts for

collaborators

22 papers

cs.RO20241 cited

Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation

Homanga Bharadhwaj, Debidatta Dwibedi, Abhinav Gupta +7

How can robot manipulation policies generalize to novel tasks involving unseen object types and new motions? In this paper, we provide a solution in terms of predicting motion info…

cs.RO20241 cited

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches

Priya Sundaresan, Quan Vuong, Jiayuan Gu +10

Natural language and images are commonly used as goal representations in goal-conditioned imitation learning (IL). However, natural language can be ambiguous and images can be over…

cs.LG2024

Batch Active Learning of Reward Functions from Human Preferences

Erdem Bıyık, Nima Anari, Dorsa Sadigh

Data generation and labeling are often expensive in robot learning. Preference-based learning is a concept that enables reliable labeling by querying users with preference question…

cs.RO202452 cited

Generative Expressive Robot Behaviors using Large Language Models

Karthik Mahadevan, Jonathan Chien, Noah Brown +6

People employ expressive behaviors to effectively communicate and coordinate their actions with others, such as nodding to acknowledge a person glancing at them or saying "excuse m…

cs.CV20245 cited

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities

Boyuan Chen, Zhuo Xu, Sean Kirmani +6

Understanding and reasoning about spatial relationships is a fundamental capability for Visual Question Answering (VQA) and robotics. While Vision Language Models (VLM) have demons…

cs.RO20231 cited

Stabilize to Act: Learning to Coordinate for Bimanual Manipulation

Jennifer Grannen, Yilin Wu, Brandon Vu +1

Key to rich, dexterous manipulation in the real world is the ability to coordinate control across two hands. However, while the promise afforded by bimanual robotic systems is imme…