Invariant EKF

EKF: Extended Kalman Filter

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Overview

Invariant extended Kalman filters represent state errors on Lie groups such as SE(3), which can make error propagation less dependent on the estimated trajectory. Methods include left- and right-invariant error models, iterated measurement updates, and adaptive noise estimation, often combining IMUs with leg kinematics, encoders, or landmarks. These filters support state estimation for legged and humanoid robots, manipulators, and inertial navigation, where accuracy and consistency matter under changing motion and contact conditions. A central open tension is that geometric formulations can improve convergence or consistency, but do not always outperform conventional EKFs in positioning accuracy, while learned or residual-based noise adaptation adds complexity.

Latest papers

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12 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Consistent Distributed Invariant EKF SLAM with Point and Object Features

    Oct 22, 2026Mengya Xu, Xianjia Yu, Ha Sier +2Simultaneous Localization and MappingInvariant EKF

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

    Sep 25, 2026Wei Ouyang, Jiale Han, Yarong Luo +1Equivariant FilteringInvariant 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

  3. Residual-Based Adaptive Kalman Filtering for Legged Robot State Estimation

    Aug 3, 2026Mihaela Popescu, Dennis Mronga, Shivesh Kumar +1Legged RoboticsKalman Filtering

  4. Derivations of Error-State Kalman Filter Kinematics for Globally Applicable Aided Inertial Navigation Systems

    Jul 3, 2026Antonia Hager, Torleiv H. BryneKalman FilteringError-State Kalman Filtering

    Airbus Central Research and Technology, Taufkirchen, Germany · Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway

  5. Iterated Invariant EKF for 3D Landmark-Aided Inertial Navigation

    Jun 30, 2026Hilton Marques Souza Santana, João Carlos Virgolino Soares, Marco Antonio MeggiolaroInvariant EKFInertial Navigation

    Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil · Dynamic Legged Systems Lab, Istituto Italiano di Tecnologia, Genova, Italy

  6. Invariant Kalman filtering for extended pose estimation in multi-IMU articulated rigid-body systems

    Jun 23, 2026Sven Goffin, Cédric Schwartz, Silvère Bonnabel +23D Human Pose EstimationHuman Pose Estimation

    Department of Electrical Engineering and Computer Science, University of Liège, Belgium · Department of Physical Activity and Rehabilitation Sciences, University of Liège, Belgium · Department of Mathematics and Systems, Mines Paris – PSL, France +1

  7. Invariant Stochastic Filtering on SE(3) for Inertial-Encoder State Estimation of Serial Rigid Manipulators

    Jun 21, 2026S. Yaqubi, M. Hejrati, J. MattilaRobot State EstimationInvariant EKF

    Department of Automation Technology and Mechanical Engineering, Tampere University, Korkeakoulunkatu 6, 33720 Tampere, Finland

  8. Proprioceptive Invariant State Estimation for Humanoid Robots on Non-Inertial Ground

    Jun 17, 2026Falak Mandali, Zijian He, Yan GuRobot State EstimationInvariant EKF

    Purdue University, West Lafayette, IN 47907, USA.

  9. CoCo-InEKF: State Estimation with Learned Contact Covariances in Dynamic, Contact-Rich Scenarios

    May 14, 2026Michael Baumgartner, David Müller, Agon Serifi +4Legged RoboticsRobot State Estimation

    ETH Zurich, Switzerland · Disney Research, Switzerland

  10. A Proprioceptive-Only Benchmark for Quadruped State Estimation: ATE, RPE, and Runtime Trade-offs Between Filters and Smoothers

    May 12, 2026Ylenia Nisticò, João Carlos Virgolino Soares, Joan Solà +1State TrackingRobot State Estimation

    Dynamic Legged Systems (DLS) Lab, Istituto Italiano di Tecnologia, 16163 Genova, Italy · Institut de Rob`otica i Inform`atica Industrial - CSIC, 08028 Barcelona, Spain

  11. Iterated Invariant EKF for Quadruped Robot Odometry

    Apr 16, 2026Hilton Marques Souza Santana, João Carlos Virgolino Soares, Sven Goffin +4Robot State EstimationInvariant EKF

    Dynamic Legged Systems Lab, Istituto Italiano di Tecnologia, Genoa, Italy. · Department of Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Brazil. · Department of Electrical Engineering and Computer Science, University of Liège, Belgium. +1

  12. Neural Aided Adaptive Innovation-Based Invariant Kalman Filter

    Mar 17, 2026Barak Diker, Itzik KleinKalman FilteringInvariant EKF