Marginalizing and Conditioning Gaussians onto Linear Approximations of Smooth Manifolds with Applications in Robotics

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Marginalizing and Conditioning Gaussians onto Linear Approximations of Smooth Manifolds with Applications in Robotics

15 September 2024

James R. Forbes

Timothy D. Barfoot

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Papers citing "Marginalizing and Conditioning Gaussians onto Linear Approximations of Smooth Manifolds with Applications in Robotics"

9 / 9 papers shown

Title
GMKF: Generalized Moment Kalman Filter for Polynomial Systems with Arbitrary Noise Sangli Teng Harry Zhang David Jin A. Jasour Maani Ghaffari Luca Carlone 115 11 0 07 Mar 2024
Data-Driven Batch Localization and SLAM Using Koopman Linearization Zi Cong Guo Frederike Dumbgen James R. Forbes Timothy D. Barfoot 69 4 0 08 Sep 2023
Koopman Kernel Regression Petar Bevanda Maximilian Beier Armin Lederer Stefan Sosnowski Eyke Hüllermeier Sandra Hirche AI4TS 59 16 0 25 May 2023
Koopman Linearization for Data-Driven Batch State Estimation of Control-Affine Systems Zixiang Guo Vassili Korotkine James R. Forbes Timothy D. Barfoot 85 12 0 14 Sep 2021
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments Ransalu Senanayake Maneekwan Toyungyernsub Mingyu Wang Mykel J. Kochenderfer Mac Schwager 65 6 0 01 Jul 2020
Learning Stable Models for Prediction and Control Giorgos Mamakoukas Ian Abraham Todd Murphey 78 39 0 08 May 2020
A micro Lie theory for state estimation in robotics J. Solà Jeremie Deray Dinesh Atchuthan 48 413 0 04 Dec 2018
Directional grid maps: modeling multimodal angular uncertainty in dynamic environments Ransalu Senanayake F. Ramos 54 27 0 03 Sep 2018
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi Yoshinobu Kawahara Takehisa Yairi 49 374 0 12 Oct 2017