Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors
| dc.contributor.advisor | Patel, Amir | |
| dc.contributor.author | Ku, Do Yeou | |
| dc.date.accessioned | 2022-10-21T11:31:32Z | |
| dc.date.available | 2022-10-21T11:31:32Z | |
| dc.date.issued | 2020 | |
| dc.date.updated | 2022-10-21T06:57:55Z | |
| dc.description.abstract | 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. | |
| dc.identifier.apacitation | Ku, D. Y. (2020). <i>Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors</i>. (). ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/36851 | en_ZA |
| dc.identifier.chicagocitation | Ku, Do Yeou. <i>"Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors."</i> ., ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2020. http://hdl.handle.net/11427/36851 | en_ZA |
| dc.identifier.citation | Ku, D.Y. 2020. Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors. . ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. http://hdl.handle.net/11427/36851 | en_ZA |
| dc.identifier.ris | TY - Master Thesis AU - Ku, Do Yeou AB - 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. DA - 2020_ DB - OpenUCT DP - University of Cape Town KW - MOCAP KW - MEMS-IMU KW - Kalman KW - single-differenced KW - double-differenced KW - DGPS KW - LAMBDA LK - https://open.uct.ac.za PY - 2020 T1 - Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors TI - Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors UR - http://hdl.handle.net/11427/36851 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/36851 | |
| dc.identifier.vancouvercitation | Ku DY. Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors. []. ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2020 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/36851 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Electrical Engineering | |
| dc.publisher.faculty | Faculty of Engineering and the Built Environment | |
| dc.subject | MOCAP | |
| dc.subject | MEMS-IMU | |
| dc.subject | Kalman | |
| dc.subject | single-differenced | |
| dc.subject | double-differenced | |
| dc.subject | DGPS | |
| dc.subject | LAMBDA | |
| dc.title | Kinematic State Estimation using Multiple DGPS/MEMS-IMU Sensors | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationlevel | MSc |