Treffer: An Open-Source Test Environment for Effective Development of MARG-Based Algorithms.

Title:
An Open-Source Test Environment for Effective Development of MARG-Based Algorithms.
Authors:
Odry Á; Department of Control Engineering and Information Technology, University of Dunaújváros, Táncsics Mihály u. 1, 2400 Dunaújváros, Hungary.
Source:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2021 Feb 08; Vol. 21 (4). Date of Electronic Publication: 2021 Feb 08.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: PubMed not MEDLINE; MEDLINE
Imprint Name(s):
Original Publication: Basel, Switzerland : MDPI, c2000-
References:
Sensors (Basel). 2020 Oct 09;20(20):. (PMID: 33050148)
Sensors (Basel). 2020 Feb 01;20(3):. (PMID: 32024177)
Sensors (Basel). 2021 Feb 08;21(4):. (PMID: 33567563)
IEEE Int Conf Rehabil Robot. 2011;2011:5975346. (PMID: 22275550)
Sensors (Basel). 2015 Aug 06;15(8):19302-30. (PMID: 26258778)
IEEE Trans Instrum Meas. 2012 Jan 8;61(8):2262-2273. (PMID: 22977288)
Sensors (Basel). 2017 Sep 19;17(9):. (PMID: 28925979)
Sensors (Basel). 2015 Sep 15;15(9):23168-87. (PMID: 26389900)
Sensors (Basel). 2020 Oct 29;20(21):. (PMID: 33138049)
Gait Posture. 2012 Jan;35(1):138-42. (PMID: 22047775)
Sensors (Basel). 2019 Mar 18;19(6):. (PMID: 30889787)
Contributed Indexing:
Keywords: Kalman filter; MARG; attitude estimation; complementary filter; inertial measurement unit; sensor fusion; test environment
Entry Date(s):
Date Created: 20210211 Date Completed: 20210212 Latest Revision: 20210304
Update Code:
20250114
PubMed Central ID:
PMC7919258
DOI:
10.3390/s21041183
PMID:
33567563
Database:
MEDLINE

Weitere Informationen

This paper presents an open-source environment for development, tuning, and performance evaluation of magnetic, angular rate, and gravity-based (MARG-based) filters, such as pose estimators and classification algorithms. The environment is available in both ROS/Gazebo and MATLAB/Simulink, and it contains a six-degrees of freedom (6 DOF) test bench, which simultaneously moves and rotates an MARG unit in the three-dimensional (3D) space. As the quality of MARG-based estimation becomes crucial in dynamic situations, the proposed test platform intends to simulate different accelerating and vibrating circumstances, along with realistic magnetic perturbation events. Moreover, the simultaneous acquisition of both the real pose states (ground truth) and raw sensor data is supported during these simulated system behaviors. As a result, the test environment executes the desired mixture of static and dynamic system conditions, and the provided database fosters the effective analysis of sensor fusion algorithms. The paper systematically describes the structure of the proposed test platform, from mechanical properties, over mathematical modeling and joint controller synthesis, to implementation results. Additionally, a case study is presented of the tuning of popular attitude estimation algorithms to highlight the advantages of the developed open-source environment.