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What is Few-Shot Learning for Granular Material Scooping about?

This paper presents a novel adaptive scooping strategy for autonomous landers sampling granular materials on extraterrestrial bodies, addressing challenges posed by domain shifts. The method utilizes a deep Gaussian process trained with a meta-learning approach called CoDeGa, allowing robots to learn from limited experiences on target terrains and achieve high-quality scooping actions. A dataset of 6,700 executed scoops on diverse materials is also provided for future research in granular material manipulat

Author

gokul

Language

EN