Christopher Doer

Papers

Total Citations

182

H-Index

About

Christopher Doer is a robotics researcher whose work centers on robust autonomous navigation, with a particular focus on localization in environments where conventional sensing modalities fail. His most significant contributions lie in the development of radar-inertial odometry systems that enable reliable positioning in GNSS-denied and visually degraded conditions — scenarios where fog, smoke, darkness, or direct sunlight render camera-based approaches ineffective. By fusing millimeter-wave FMCW radar with Inertial Measurement Unit (IMU) data through Extended Kalman Filter (EKF) frameworks, Doer has advanced the state of the art in resilient robot localization. His 2020 paper introducing an EKF-based radar inertial odometry approach has garnered 109 citations, establishing it as a foundational reference in the field, while his follow-up work on online calibration (46 citations) and Manhattan World-assisted yaw estimation (25 citations) demonstrate a sustained and deepening research trajectory. Beyond ground-level navigation, Doer has also contributed to aerial robotics, including control algorithm development for rescue UAVs. His body of work reflects a strong commitment to bridging theoretical sensor fusion techniques with real-world autonomous systems applications, making him a valuable voice in the robotics navigation community.