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Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors
Animals have evolved over billions of years and understanding these complex and intertwined systems have potential to advance the technology in the field of sports science, robotics and more. As such, a gait analysis using Motion Capture (MOCAP) technology is the subject of a number of research and...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2022
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| _version_ | 1867613258363437056 |
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| access_status_str | Open Access |
| author | Ku, Do Yeou |
| author2 | Patel, Amir |
| author_browse | Ku, Do Yeou Patel, Amir |
| author_facet | Patel, Amir Ku, Do Yeou |
| author_sort | Ku, Do Yeou |
| collection | Thesis |
| description | Animals have evolved over billions of years and understanding these complex and intertwined systems have potential to advance the technology in the field of sports science, robotics and more. As such, a gait analysis using Motion Capture (MOCAP) technology is the subject of a number of research and development projects aimed at obtaining quantitative measurements. Existing MOCAP technology has limited the majority of studies to the analysis of the steady-state locomotion in a controlled (indoor) laboratory environment. MOCAP systems such as the optical, non-optical acoustic and non-optical magnetic MOCAP systems require predefined capture volume and controlled environmental conditions whilst the non-optical mechanical MOCAP system impedes the motion of the subject. Although the non-optical inertial MOCAP system allows MOCAP in an outdoor environment, it suffers from measurement noise and drift and lacks global trajectory information. The accuracy of these MOCAP systems are known to decrease during the tracking of the transient locomotion. Quantifying the manoeuvrability of animals in their natural habitat to answer the question “Why are animals so manoeuvrable?” remains a challenge. This research aims to develop an outdoor MOCAP system that will allow tracking of the steady-state as well as the transient locomotion of an animal in its natural habitat outside a controlled laboratory condition. A number of researchers have developed novel MOCAP systems with the same aim of creating an outdoor MOCAP system that is aimed at tracking the motion outside a controlled laboratory (indoor) environment with unlimited capture volume. These novel MOCAP systems are either not validated against the commercial MOCAP systems or do not have comparable sub-millimetre accuracy as the commercial MOCAP systems. The developed DGPS/MEMS-IMU multi-receiver fusion MOCAP system was assessed to have global trajectory accuracy of _0:0394m, relative limb position accuracy of _0:006497m. To conclude the research, several recommendations are made to improve the developed MOCAP system and to prepare for a field-testing with a wild animal from a family of a terrestrial megafauna. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/36851 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:17.409Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/36851 Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors Ku, Do Yeou Patel, Amir MOCAP MEMS-IMU Kalman single-differenced double-differenced DGPS LAMBDA Animals have evolved over billions of years and understanding these complex and intertwined systems have potential to advance the technology in the field of sports science, robotics and more. As such, a gait analysis using Motion Capture (MOCAP) technology is the subject of a number of research and development projects aimed at obtaining quantitative measurements. Existing MOCAP technology has limited the majority of studies to the analysis of the steady-state locomotion in a controlled (indoor) laboratory environment. MOCAP systems such as the optical, non-optical acoustic and non-optical magnetic MOCAP systems require predefined capture volume and controlled environmental conditions whilst the non-optical mechanical MOCAP system impedes the motion of the subject. Although the non-optical inertial MOCAP system allows MOCAP in an outdoor environment, it suffers from measurement noise and drift and lacks global trajectory information. The accuracy of these MOCAP systems are known to decrease during the tracking of the transient locomotion. Quantifying the manoeuvrability of animals in their natural habitat to answer the question “Why are animals so manoeuvrable?” remains a challenge. This research aims to develop an outdoor MOCAP system that will allow tracking of the steady-state as well as the transient locomotion of an animal in its natural habitat outside a controlled laboratory condition. A number of researchers have developed novel MOCAP systems with the same aim of creating an outdoor MOCAP system that is aimed at tracking the motion outside a controlled laboratory (indoor) environment with unlimited capture volume. These novel MOCAP systems are either not validated against the commercial MOCAP systems or do not have comparable sub-millimetre accuracy as the commercial MOCAP systems. The developed DGPS/MEMS-IMU multi-receiver fusion MOCAP system was assessed to have global trajectory accuracy of _0:0394m, relative limb position accuracy of _0:006497m. To conclude the research, several recommendations are made to improve the developed MOCAP system and to prepare for a field-testing with a wild animal from a family of a terrestrial megafauna. 2022-10-21T11:31:32Z 2022-10-21T11:31:32Z 2020 2022-10-21T06:57:55Z Master Thesis Masters MSc http://hdl.handle.net/11427/36851 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment |
| spellingShingle | MOCAP MEMS-IMU Kalman single-differenced double-differenced DGPS LAMBDA Ku, Do Yeou Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| thesis_degree_str | Master's |
| title | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| title_full | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| title_fullStr | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| title_full_unstemmed | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| title_short | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors |
| title_sort | kinematic state estimation using multiple dgps mems imu sensors |
| topic | MOCAP MEMS-IMU Kalman single-differenced double-differenced DGPS LAMBDA |
| url | http://hdl.handle.net/11427/36851 |
| work_keys_str_mv | AT kudoyeou kinematicstateestimationusingmultipledgpsmemsimusensors |