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About

Jeff Delaune is a robotics researcher specializing in autonomous navigation, state estimation, and perception systems for aerial robots operating in extreme environments — most notably planetary exploration platforms. His work sits at the intersection of computer vision, inertial sensing, and multi-agent autonomy, with a particular focus on enabling robust flight in conditions that challenge conventional sensors. Delaune has made significant contributions to vision-based navigation for Mars rotorcraft, including pioneering work on event camera-based odometry — a technology well-suited to the motion blur and lighting extremes encountered during planetary flight — which has garnered 69 citations and established him as a leading voice in this emerging area. His research on autonomous safe landing site detection and multi-resolution elevation mapping (each with 17 citations) directly addresses critical mission requirements for future Mars science helicopters. He has also contributed to multi-robot autonomy through NASA's CADRE lunar demonstration mission, exploring how teams of rovers can operate collaboratively and independently. Beyond planetary systems, Delaune has advanced decentralized thermal-inertial odometry for UAV teams and developed the INSANE benchmark datasets to support robust localization research across diverse environments. His cumulative impact reflects a research program that bridges theoretical innovation with real-world deployment on some of humanity's most ambitious robotic exploration missions.