A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking
In 3D motion capture, multiple methods have been developed in order to optimize the quality of the captured data. While certain technologies, such as inertial measurement units (IMU), are mostly suitable for 3D orientation estimation at relatively high frequencies, other technologies, such as marker...
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| Format: | Article |
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MDPI AG
2020-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/20/5864 |
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| author | Gia-Hoang Phan Clint Hansen Paolo Tommasino Asif Hussain Domenico Formica Domenico Campolo |
| author_facet | Gia-Hoang Phan Clint Hansen Paolo Tommasino Asif Hussain Domenico Formica Domenico Campolo |
| author_sort | Gia-Hoang Phan |
| collection | DOAJ |
| description | In 3D motion capture, multiple methods have been developed in order to optimize the quality of the captured data. While certain technologies, such as inertial measurement units (IMU), are mostly suitable for 3D orientation estimation at relatively high frequencies, other technologies, such as marker-based motion capture, are more suitable for 3D position estimations at a lower frequency range. In this work, we introduce a complementary filter that complements 3D motion capture data with high-frequency acceleration signals from an IMU. While the local optimization reduces the error of the motion tracking, the additional accelerations can help to detect micro-motions that are useful when dealing with high-frequency human motions or robotic applications. The combination of high-frequency accelerometers improves the accuracy of the data and helps to overcome limitations in motion capture when micro-motions are not traceable with 3D motion tracking system. In our experimental evaluation, we demonstrate the improvements of the motion capture results during translational, rotational, and combined movements. |
| first_indexed | 2024-03-10T15:33:06Z |
| format | Article |
| id | doaj.art-045c2f5fd61e423fbdbc77f5d30906d3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:33:06Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-045c2f5fd61e423fbdbc77f5d30906d32023-11-20T17:24:39ZengMDPI AGSensors1424-82202020-10-012020586410.3390/s20205864A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion TrackingGia-Hoang Phan0Clint Hansen1Paolo Tommasino2Asif Hussain3Domenico Formica4Domenico Campolo5Industrial Maintenance Training Center, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, C1/268, Ho Chi Minh City 70000, VietnamNeurogeriatrics Kiel, Department of Neurology, University Hospital of Kiel, 24105 Kiel, GermanyLaboratory of Neuromotor Physiology, I.R.C.C.S. Fondazione Santa Lucia, 00179 Rome, ItalyRobotics Research Center, Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, SingaporeCentre for Integrated Research, Università Campus Bio-Medico di Roma, 00128 Rome, ItalyRobotics Research Center, Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, SingaporeIn 3D motion capture, multiple methods have been developed in order to optimize the quality of the captured data. While certain technologies, such as inertial measurement units (IMU), are mostly suitable for 3D orientation estimation at relatively high frequencies, other technologies, such as marker-based motion capture, are more suitable for 3D position estimations at a lower frequency range. In this work, we introduce a complementary filter that complements 3D motion capture data with high-frequency acceleration signals from an IMU. While the local optimization reduces the error of the motion tracking, the additional accelerations can help to detect micro-motions that are useful when dealing with high-frequency human motions or robotic applications. The combination of high-frequency accelerometers improves the accuracy of the data and helps to overcome limitations in motion capture when micro-motions are not traceable with 3D motion tracking system. In our experimental evaluation, we demonstrate the improvements of the motion capture results during translational, rotational, and combined movements.https://www.mdpi.com/1424-8220/20/20/5864complementary filterinertia-measurement unitload cellmotion trackingsensor fusionvalidation |
| spellingShingle | Gia-Hoang Phan Clint Hansen Paolo Tommasino Asif Hussain Domenico Formica Domenico Campolo A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking Sensors complementary filter inertia-measurement unit load cell motion tracking sensor fusion validation |
| title | A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking |
| title_full | A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking |
| title_fullStr | A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking |
| title_full_unstemmed | A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking |
| title_short | A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking |
| title_sort | complementary filter design on se 3 to identify micro motions during 3d motion tracking |
| topic | complementary filter inertia-measurement unit load cell motion tracking sensor fusion validation |
| url | https://www.mdpi.com/1424-8220/20/20/5864 |
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