Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


2023_thesis_chengkun_liu.pdf (4.04 MB)

Digital Accessibility Report

File List


Dissertation_chengkun_2023.pdf.accreport__approved.html (19.34 KB)

ETD Abstract Container

Abstract Header

Data Fusion of Ultra-Wideband Signals and Inertial Measurement Unit for Real-Time Localization

Chengkun, Liu
http://orcid.org/0000-0002-1877-8289
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1690904640383541

Abstract Details

2023, Doctor of Philosophy (Ph.D.), University of Dayton, Electrical Engineering.
Autonomous systems usually require accurate localization methods for them to navigate safely in indoor environments. Most localization methods are expensive and difficult to set up. In this work, we built a low-cost and portable indoor location tracking system by using Raspberry Pi 4 computer, ultra-wideband (UWB) sensors, and inertial measurement unit(s) (IMU). We also developed the data logging software and the 2D Kalman filter (KF) sensor fusion algorithm to process the data from a low-power UWB transceiver (Decawave, model DWM1001) module and IMU device (Bosch, model BNO055). Autonomous systems move with different velocities and accelerations, which requires their localization performance to be evaluated under diverse motion conditions. We built a dynamic testing platform to generate not only the ground truth trajectory but also the ground truth acceleration and velocity. In this way, our tracking system's localization performance can be evaluated under dynamic testing conditions. The novel contributions in this work are a low-cost, low-power, tracking system hardware and software design, and a 2D linear stage experimental setup to observe the tracking system's localization performance under different dynamic testing conditions. The 2D testing platform has a 1 m translation length and 80 micrometers of bidirectional repeatability. The tracking system's localization performance is evaluated under dynamic conditions with eight different combinations of acceleration and velocity. The ground truth accelerations varied from 0.6 to 1.6 m/s$^2$ and the ground truth velocities varied from 0.6 to 0.8 m/s. Our experimental results show that the location error can reach up to 50 cm under dynamic testing conditions when only relying on the UWB sensor, with the KF sensor fusion of UWB and IMU, the location error decreases to 13.7 cm. For autonomous systems which require 3D real-time locating service, a 3D tracking device is designed based on the previously mentioned 2D tracking device. The consumer grade IMU BNO055 is replaced by a tactical grade IMU ADIS16495, while the other system parts stay the same. The 3D tracking device requires to run a 3D Kalman filter. The 3D Kalman filter is modified from the 2D Kalman filter by adding one more dimension to its state vector and motion model. An industry standard robotic arm YASKAWA GP7 is selected for generating the 3D ground truth trajectory. The 3D tracking device is attached to the robotic arm to evaluate its 3D localization performance.
Vamsy. Chodavarapu, Prof. (Advisor)
Manish. Kumar, Prof. (Committee Member)
Raul. Ordonez, Prof. (Committee Member)
Vijayan K. Asari, Prof. (Committee Member)
106 p.
Electrical Engineering
UWB; IMU; Localization; 2D Kalman filter; 3D Kalman filter

Recommended Citations

Citations

  • Chengkun, L. (2023). Data Fusion of Ultra-Wideband Signals and Inertial Measurement Unit for Real-Time Localization [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1690904640383541

    APA Style (7th edition)

  • Chengkun, Liu. Data Fusion of Ultra-Wideband Signals and Inertial Measurement Unit for Real-Time Localization . 2023. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1690904640383541.

    MLA Style (8th edition)

  • Chengkun, Liu. "Data Fusion of Ultra-Wideband Signals and Inertial Measurement Unit for Real-Time Localization ." Doctoral dissertation, University of Dayton, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1690904640383541

    Chicago Manual of Style (17th edition)

dayton1690904640383541
140
© 2023, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.