Localization of cyborg insects using IMU-based method

This thesis explores the use of Inertial Measurement Unit (IMU) systems to track the movement trajectories of cyborg insects, with a particular focus on IMU-equipped cockroaches. The objective of this research is to accurately localise and track these insects in a controlled indoor environment using...

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Bibliographic Details
Main Author: Fan, Zifu
Other Authors: Hirotaka Sato
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
IMU
Online Access:https://hdl.handle.net/10356/177563
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1775632024-06-01T16:52:00Z Localization of cyborg insects using IMU-based method Fan, Zifu Hirotaka Sato School of Mechanical and Aerospace Engineering hirosato@ntu.edu.sg Engineering IMU Cyborg insects Positioning This thesis explores the use of Inertial Measurement Unit (IMU) systems to track the movement trajectories of cyborg insects, with a particular focus on IMU-equipped cockroaches. The objective of this research is to accurately localise and track these insects in a controlled indoor environment using data-driven machine learning techniques and the VICON motion capture system. In order to improve the reliability of the data, this study employs advanced pre-processing techniques, including wavelet denoising, to refine the IMU data prior to analysis. The core of the study is the development of a random forest regression model that is trained to predict cyborg insect movement based on features extracted from the processed IMU data. The model was validated against data collected by the VICON system, which provides highly accurate spatial localization. The results of the study indicate that while the model provides a reasonably high level of accuracy with respect to standard motion patterns, it encounters limitations with respect to complex movements (especially fast, nonlinear motions). Future work will aim to enhance the model's ability to handle diverse and dynamic motion patterns, and potentially extend it to 3D tracking for more complex environments. This research establishes a foundational approach that combines machine learning with traditional motion tracking techniques and is an important step forward in the automation and accuracy of insect motion analysis. Bachelor's degree 2024-05-29T09:34:49Z 2024-05-29T09:34:49Z 2024 Final Year Project (FYP) Fan, Z. (2024). Localization of cyborg insects using IMU-based method. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177563 https://hdl.handle.net/10356/177563 en B084 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
IMU
Cyborg insects
Positioning
spellingShingle Engineering
IMU
Cyborg insects
Positioning
Fan, Zifu
Localization of cyborg insects using IMU-based method
description This thesis explores the use of Inertial Measurement Unit (IMU) systems to track the movement trajectories of cyborg insects, with a particular focus on IMU-equipped cockroaches. The objective of this research is to accurately localise and track these insects in a controlled indoor environment using data-driven machine learning techniques and the VICON motion capture system. In order to improve the reliability of the data, this study employs advanced pre-processing techniques, including wavelet denoising, to refine the IMU data prior to analysis. The core of the study is the development of a random forest regression model that is trained to predict cyborg insect movement based on features extracted from the processed IMU data. The model was validated against data collected by the VICON system, which provides highly accurate spatial localization. The results of the study indicate that while the model provides a reasonably high level of accuracy with respect to standard motion patterns, it encounters limitations with respect to complex movements (especially fast, nonlinear motions). Future work will aim to enhance the model's ability to handle diverse and dynamic motion patterns, and potentially extend it to 3D tracking for more complex environments. This research establishes a foundational approach that combines machine learning with traditional motion tracking techniques and is an important step forward in the automation and accuracy of insect motion analysis.
author2 Hirotaka Sato
author_facet Hirotaka Sato
Fan, Zifu
format Final Year Project
author Fan, Zifu
author_sort Fan, Zifu
title Localization of cyborg insects using IMU-based method
title_short Localization of cyborg insects using IMU-based method
title_full Localization of cyborg insects using IMU-based method
title_fullStr Localization of cyborg insects using IMU-based method
title_full_unstemmed Localization of cyborg insects using IMU-based method
title_sort localization of cyborg insects using imu-based method
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/177563
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