FastGrasp uses two-stage RL with CVAE for diverse grasp candidates from point clouds and tactile sensing for impact adjustments to achieve robust fast whole-body grasping in sim and real-world settings.
Hands for dexterous manipulation and robust grasping: A difficult road toward simplicity,
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The paper introduces micro-dexterity as a framework for biological micromanipulation by reformulating classical primitives in fluidic, surface-dominated micro-environments and comparing contact-based, field-mediated, and multi-agent architectures.
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FastGrasp: Learning-based Whole-body Control method for Fast Dexterous Grasping with Mobile Manipulators
FastGrasp uses two-stage RL with CVAE for diverse grasp candidates from point clouds and tactile sensing for impact adjustments to achieve robust fast whole-body grasping in sim and real-world settings.
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Micro-Dexterity in Biological Micromanipulation: Embodiment, Perception, and Control
The paper introduces micro-dexterity as a framework for biological micromanipulation by reformulating classical primitives in fluidic, surface-dominated micro-environments and comparing contact-based, field-mediated, and multi-agent architectures.