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TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation
This problem is more severe in mobile manipulation, where collecting demonstrations is harder than in stationary manipulation due to the lack of available and easy-to-use teleoperation interfaces.
Model-Based Runtime Monitoring with Interactive Imitation Learning
Unlike prior work that cannot foresee future failures or requires failure experiences for training, our method learns a latent-space dynamics model and a failure classifier, enabling our method to simulate future action outcomes and detect out-of-distribution and high-risk states preemptively.
PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection
Large-scale data is an essential component of machine learning as demonstrated in recent advances in natural language processing and computer vision research.
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