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Title: | Nonlinear filter for simultaneous localization and mapping on a matrix lie group using IMU and feature measurements | Authors: | Hashim, HA Eltoukhy, AEE |
Issue Date: | Apr-2022 | Source: | IEEE transactions on systems, man, and cybernetics. Systems, Apr. 2022, v. 52, no. 4, p. 2098-2109 | Abstract: | Simultaneous localization and mapping (SLAM) is a process of concurrent estimation of the vehicle's pose and feature locations with respect to a frame of reference. This article proposes a computationally cheap geometric nonlinear SLAM filter algorithm structured to mimic the nonlinear motion dynamics of the true SLAM problem posed on the matrix Lie group of SLAMn(3). The nonlinear filter on manifold is proposed in continuous form and it utilizes available measurements obtained from group velocity vectors, feature measurements, and an inertial measurement unit (IMU). The unknown bias attached to velocity measurements is successfully handled by the proposed estimator. Simulation results illustrate the robustness of the proposed filter in discrete form, demonstrating its utility for the six-degrees-of-freedom (6 DoF) pose estimation as well as feature estimation in three-dimensional (3-D) space. In addition, the quaternion representation of the nonlinear filter for SLAM is provided. | Keywords: | Inertial measurement unit (IMU) Inertial vision system Nonlinear observer algorithm for SLAM Simultaneous localization and mapping (SLAM) Special Euclidean group [SE(3)] Special orthogonal group [SO(3)] |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE Transactions on Systems, Man, and Cybernetics: Systems | ISSN: | 2168-2216 | EISSN: | 2168-2232 | DOI: | 10.1109/TSMC.2020.3047338 | Rights: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Hashim, H. A., & Eltoukhy, A. E. (2021). Nonlinear filter for simultaneous localization and mapping on a matrix lie group using imu and feature measurements. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(4), 2098-2109 is available at https://doi.org/10.1109/TSMC.2020.3047338 |
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