15 citations · 20 across the 5 of their papers we have counts for
6 papers
Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay
Giulio Delama, Martin Scheiber, Yixiao Ge +3
Many Inertial Navigation Systems (INS) use Global Navigation Satellite System (GNSS) position as the primary measurement to drive filter performance and bound error growth. However…
Equivariant Filter for Radar-Inertial Odometry
Giulio Delama, Jan Michalczyk, Morten Nissov +4
Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Measurement Unit (IMU) and is se…
The Difference between the Left and Right Invariant Extended Kalman Filter
Yixiao Ge, Giulio Delama, Martin Scheiber +4
The extended Kalman filter (EKF) has been the industry standard for state estimation problems over the past sixty years. The Invariant Extended Kalman Filter (IEKF) is a recent dev…
AIVIO: Closed-loop, Object-relative Navigation of UAVs with AI-aided Visual Inertial Odometry
Thomas Jantos, Martin Scheiber, Christian Brommer +3
Object-relative mobile robot navigation is essential for a variety of tasks, e.g. autonomous critical infrastructure inspection, but requires the capability to extract semantic inf…
Revisiting multi-GNSS Navigation for UAVs -- An Equivariant Filtering Approach
Martin Scheiber, Alessandro Fornasier, Christian Brommer +1
In this work, we explore the recent advances in equivariant filtering for inertial navigation systems to improve state estimation for uncrewed aerial vehicles (UAVs). Traditional s…
INSANE: Cross-Domain UAV Data Sets with Increased Number of Sensors for developing Advanced and Novel Estimators
Christian Brommer, Alessandro Fornasier, Martin Scheiber +4
For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust…