HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.
Learning visuotactile skills with two multifingered hands,
2 Pith papers cite this work. Polarity classification is still indexing.
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A two-room Wizard-of-Oz pilot collected 53 multimodal trials from five users to capture dialogue ambiguities for training ambiguity-aware assistive robot controllers.
citing papers explorer
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Learning Versatile Humanoid Manipulation with Touch Dreaming
HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.
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A Multimodal Data Collection Framework for Dialogue-Driven Assistive Robotics to Clarify Ambiguities: A Wizard-of-Oz Pilot Study
A two-room Wizard-of-Oz pilot collected 53 multimodal trials from five users to capture dialogue ambiguities for training ambiguity-aware assistive robot controllers.