Equivariant Filtering

Latest papers

8 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Accuracy Evaluation of INS/ZUPT Filtering Methods Based on Different Geometric Error Definitions
Sep 25, 2026Wei Ouyang, Jiale Han, Yarong Luo +1Equivariant Filtering Invariant EKF
School of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China · School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China · School of Robotics, Wuhan University, Wuhan 430072, China
Equivariant Filter Design for Acoustic and Depth Aided Inertial Navigation Systems
Sep 17, 2026Arihant Lunawat, Pieter van Goor, Frank Dellaert +1Equivariant Filtering Underwater Robotics
The University of Sydney Sydney, Australia · Georgia Tech Atlanta, USA
The Iterative Equivariant Filter
Sep 11, 2026Pieter van Goor, James Richard ForbesEquivariant Filtering Robot State Estimation
School of Aerospace, Mechanical, and Mechatronic Engineering The University of Sydney NSW 2006, Australia · Dept. of Mechanical Engineering McGill University Montreal, QC, Canada
Equivariant Filter for High Performance Image Tracking using an Event Camera
Jul 10, 2026Angus Apps, Yixiao Ge, Timothy L. Molloy +1Event-Based Vision Visual Object Tracking
Systems Theory and Robotics Group School of Engineering Australian National University Canberra, Australia · School of Engineering Australian National University Canberra, Australia
Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay
May 13, 2026Giulio Delama, Martin Scheiber, Yixiao Ge +3UAV Navigation Equivariant Filtering
Control of Networked Systems Group University of Klagenfurt 9020 Klagenfurt, Austria · Systems Theory and Robotics Group Australian National University ACT, 2601, Australia · I3S, CNRS, Universit´e Cˆote d’Azur and Institut Universitaire de France 06900 Sophia Antipolis, France
Equivariant Filter for Radar-Inertial Odometry
Apr 24, 2026Giulio Delama, Jan Michalczyk, Morten Nissov +4Inertial Odometry Equivariant Filtering
Control of Networked Systems Group, University of Klagenfurt, Austria · Autonomous Robots Lab, Norwegian University of Science and Technology, Norway · Hexagon Robotics, Zurich, Switzerland
Equivariant Filter Transformations for Consistent and Efficient Visual--Inertial Navigation
Mar 25, 2026Chungeng Tian, Fenghua He, Ning HaoEquivariant Filtering Robot Localization
School of Astronautics, Harbin Institute of Technology, Harbin, 150000, China.
Tutorial on Aided Inertial Navigation Systems: A Modern Treatment Using Lie-Group Theoretical Methods
Mar 7, 2026Soulaimane BerkaneEquivariant Filtering Inertial Navigation
Université du Québec en Outaouais · LaRSA – Robotics and Autonomous Systems Laboratory

Sep 25, 2026J/K move · Enter open · S save

Accuracy Evaluation of INS/ZUPT Filtering Methods Based on Different Geometric Error Definitions

Wei Ouyang, Jiale Han, Yarong Luo, Maoran Zhu

School of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China · School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China · School of Robotics, Wuhan University, Wuhan 430072, China

Equivariant Filtering Invariant EKF Inertial Navigation Error-State Kalman Filtering

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Geometric filters have recently been introduced to improve the accuracy and consistency of inertial-based integrated navigation systems. Error states were defined through specific group operations, introducing state correlations in error definition, which were lacked in the additive error used by a conventional indirect Kalman filter. The desirable consistent filtering models can be obtained based on specific geometric errors. For zero-velocity measurements expressed in the reference frame, this paper derives left-error process and measurement models from invariant filtering, two-frame-group filtering, and equivariant filtering. Importantly, a new group operation is introduced for the left tangent-group equivariant error. The analysis shows that the two-frame-group invariant extended Kalman filter (TFG-IEKF) and the tangent-group equivariant filter (TG-EqF) do not offer a significant consistency advantage over the invariant extended Kalman filter (IEKF). Experiments with an INS/ZUPT measurement system show that, under small initial attitude errors, the conventional indirect extended Kalman filter (EKF) achieves loop-closure position errors below

0.1\%

of the traveled distance, while the three geometric filters achieve comparable positioning accuracy.