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Aerial Manipulation in the Wild with Onboard Perception, Policy Learning, and Whole-Body Control
Aerial manipulation in outdoor environments remains challenging due to the simultaneous requirements of reliable state estimation, stable aerial motion, and precise manipulation under external disturbances. In this work, we present a real-world outdoor aerial manipulation framework that integrates i
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