orientation_estimat​ion_sensor_fusion_a​lgorithm_codes

버전 3.0 (40.5 KB) 작성자: Marco Caruso
MATLAB implementations of 10 sensor fusion algorithms for orientation estimation using magneto-inertial measurement units (MIMU).
다운로드 수: 233
업데이트 날짜: 2021/6/3
Repository containing the optimization and source open code of several sensor fusion algorithms for estimating the orientation based on inertial and magnetic sensing.
Please, refer to https://www.mdpi.com/1424-8220/21/7/2543
Caruso, M.; Sabatini, A.M.; Laidig, D.; Seel, T.; Knaflitz, M.; Della Croce, U.; Cereatti, A. Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All. Sensors 2021, 21, 2543. https://doi.org/10.3390/s21072543
Authors: Marco Caruso (marco.caruso@polito.it) PolitoBIOMed Lab – Biomedical Engineering Lab and Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy; Last modified: 03/06/2021
This repository contains the following folders and script.
SFA: open MATLAB function of each sensor fusion algorithm;
Optimization codes: function to compute the absolute orientation errors for each unit. The orientation is computed with all the combination of parameters given as input;
function_utilities: includes some MATLAB functions helpful for the algorithms.
When using these codes, please cite: M. Caruso, A. M. Sabatini, D. Laidig, T. Seel, M. Knaflitz, U. Della Croce, and A. Cereatti, “Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All,” Sensors, vol. 21, no. 7, p. 2543, Apr. 2021. https://www.mdpi.com/1424-8220/21/7/2543

인용 양식

Marco Caruso (2024). orientation_estimation_sensor_fusion_algorithm_codes (https://github.com/marcocaruso/sensor_fusion_algorithm_codes/releases/tag/v3.0), GitHub. 검색됨 .

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버전 게시됨 릴리스 정보
3.0

See release notes for this release on GitHub: https://github.com/marcocaruso/sensor_fusion_algorithm_codes/releases/tag/v3.0

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