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About

Eva Reitbauer is a robotics researcher specializing in autonomous navigation and sensor fusion for challenging, GNSS-denied environments. Her work focuses on enabling reliable positioning for agricultural and industrial vehicles where satellite signals are unreliable or unavailable. Reitbauer’s major contributions include developing robust multi-sensor fusion algorithms that integrate LiDAR, IMU, wheel odometry, and GNSS-RTK to bridge critical positioning gaps. Her 2021 study on agricultural vehicles demonstrated how to maintain centimeter-level accuracy during GNSS outages, a key enabler for fully autonomous farming. She also engineered an autonomous navigation module for tracked compost turners, addressing labor shortages in waste management. In subterranean robotics, Reitbauer designed positioning systems for semi-autonomous robots supporting emergency task forces, combining hazardous material detection with automatic site mapping to improve first responder safety. Her most recent work, LIWO-SLAM (2023), presents a factor graph optimization framework for simultaneous localization and mapping in GNSS-denied environments, extending the popular LIO-SAM algorithm with a four-wheel odometry factor. With papers accumulating citations across precision agriculture, industrial automation, and search-and-rescue robotics, Reitbauer is advancing the frontier of reliable autonomous navigation in the world’s most difficult operational conditions.