25 citations · 83 across the 13 of their papers we have counts for
13 papers
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…
Consistent Pose Estimation of Unmanned Ground Vehicles through Terrain-Aided Multi-Sensor Fusion on Geometric Manifolds
Alexander Raab, Stephan Weiss, Alessandro Fornasier +2
Aiming to enhance the consistency and thus long-term accuracy of Extended Kalman Filters for terrestrial vehicle localization, this paper introduces the Manifold Error State Extend…
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…
Sensor Model Identification via Simultaneous Model Selection and State Variable Determination
Christian Brommer, Alessandro Fornasier, Jan Steinbrener +1
We present a method for the unattended gray-box identification of sensor models commonly used by localization algorithms in the field of robotics. The objective is to determine the…
Equivariant IMU Preintegration with Biases: a Galilean Group Approach
Giulio Delama, Alessandro Fornasier, Robert Mahony +1
This letter proposes a new approach for Inertial Measurement Unit (IMU) preintegration, a fundamental building block that can be leveraged in different optimization-based Inertial…
Equivariant Symmetries for Aided Inertial Navigation
Alessandro Fornasier
Respecting the geometry of the underlying system and exploiting its symmetry have been driving concepts in deriving modern geometric filters for inertial navigation systems (INSs).…
MSCEqF: A Multi State Constraint Equivariant Filter for Vision-aided Inertial Navigation
Alessandro Fornasier, Pieter van Goor, Eren Allak +2
This letter re-visits the problem of visual-inertial navigation system (VINS) and presents a novel filter design we dub the multi state constraint equivariant filter (MSCEqF, in an…
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…
Equivariant Symmetries for Inertial Navigation Systems
Alessandro Fornasier, Yixiao Ge, Pieter van Goor +2
This paper investigates the problem of inertial navigation system (INS) filter design through the lens of symmetry. The extended Kalman filter (EKF) and its variants have been the…
UVIO: An UWB-Aided Visual-Inertial Odometry Framework with Bias-Compensated Anchors Initialization
Giulio Delama, Farhad Shamsfakhr, Stephan Weiss +2
This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide robust and low-drift localization…
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…
Overcoming Bias: Equivariant Filter Design for Biased Attitude Estimation with Online Calibration
Alessandro Fornasier, Yonhon Ng, Christian Brommer +3
Stochastic filters for on-line state estimation are a core technology for autonomous systems. The performance of such filters is one of the key limiting factors to a system's capab…
Equivariant Filter Design for Inertial Navigation Systems with Input Measurement Biases
Alessandro Fornasier, Yonhon Ng, Robert Mahony +1
Inertial Navigation Systems (INS) are a key technology for autonomous vehicles applications. Recent advances in estimation and filter design for the INS problem have exploited geom…