1 citations · 3 across the 7 of their papers we have counts for
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Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models
Huihan Liu, Rutav Shah, Shuijing Liu +6
Assistive teleoperation, where control is shared between a human and a robot, enables efficient and intuitive human-robot collaboration in diverse and unstructured environments. A…
SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning
Yu Zhang, Yuqi Xie, Huihan Liu +4
Imitation learning advances robot capabilities by enabling the acquisition of diverse behaviors from human demonstrations. However, large-scale datasets used for policy training of…
Multi-Task Interactive Robot Fleet Learning with Visual World Models
Huihan Liu, Yu Zhang, Vaarij Betala +4
Recent advancements in large-scale multi-task robot learning offer the potential for deploying robot fleets in household and industrial settings, enabling them to perform diverse t…
PRIME: Scaffolding Manipulation Tasks with Behavior Primitives for Data-Efficient Imitation Learning
Tian Gao, Soroush Nasiriany, Huihan Liu +2
Imitation learning has shown great potential for enabling robots to acquire complex manipulation behaviors. However, these algorithms suffer from high sample complexity in long-hor…
Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu +3
The ability to learn and refine behavior after deployment has become ever more important for robots as we design them to operate in unstructured environments like households. In th…
Model-Based Runtime Monitoring with Interactive Imitation Learning
Huihan Liu, Shivin Dass, Roberto Martín-Martín +1
Robot learning methods have recently made great strides, but generalization and robustness challenges still hinder their widespread deployment. Failing to detect and address potent…