Martin Scheiber
Papers
5
Total Citations
29
H-Index
4
About
Martin Scheiber is a leading researcher in autonomous aerial robotics, specializing in robust localization and navigation for unmanned aerial vehicles (UAVs) operating in challenging, real-world environments. His work centers on developing advanced sensor fusion algorithms, particularly radar-inertial and visual-inertial odometry, to enable safe, closed-loop control on resource-constrained platforms. Scheiber’s major contributions include the creation of the **INSANE dataset** (2022–2024), a comprehensive collection of multi-sensor data spanning Mars-analog, outdoor, and indoor-outdoor transition scenarios, which has already garnered 11 citations and serves as a critical benchmark for the field. He also introduced **Radar-Inertial Odometry (RIO)** for UAVs, demonstrating real-time state estimation on portable embedded computers, and **AIVIO**, an AI-aided visual-inertial odometry system for object-relative navigation. His **VINSEval** framework (2021) provides a standardized evaluation tool for testing consistency and robustness across visual-inertial navigation algorithms. With over 30 total citations across his most-cited works, Scheiber’s research is pivotal for advancing autonomous flight in GPS-denied and dynamic environments, directly impacting applications from infrastructure inspection to planetary exploration.
Research Focus
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Top Papers
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