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About

Aaron Ray is a robotics researcher whose work sits at the intersection of autonomous aerial systems, multi-robot coordination, and bio-inspired design. His key contributions span robust navigation, collaborative mapping, and agile manipulation. Ray’s most cited work, "Robust flight navigation out of distribution with liquid neural networks" (79 citations), demonstrates how autonomous robots can generalize visual navigation to unseen environments—a critical step toward real-world deployment. He also led the development of the PiDrone (37 citations), a low-cost educational platform that empowers students to build and program their own drones, making robotics education more accessible. In multi-robot systems, his Hydra-Multi framework (21 citations) enables teams of drones to collaboratively construct 3D scene graphs, advancing high-level environmental understanding. Perhaps most strikingly, Ray’s work on high-speed aerial grasping (19 citations) uses a soft drone with onboard perception to achieve bird-like agility, overcoming the limitations of rigid manipulators. With a total of over 160 citations across his top papers, Ray is shaping the future of autonomous flight—from classroom to field—by blending theoretical rigor with practical, scalable systems.