Theses and Dissertations

Author

Sheng Cai

Issuing Body

Mississippi State University

Advisor

Donohoe, J. Patrick

Committee Member

Abdelwahed, Sherif

Committee Member

Fowler, James E.

Committee Member

Li, Pan

Date of Degree

1-1-2016

Document Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

As an emerging technology, autonomous Unmanned Vehicle Systems (UVS) have found not only many military applications, but also various civil applications. For example, Google, Amazon and Facebook are developing their UVS plans to explore new markets. However, there are still a lot of challenging problems which deter the UVS’s development. We study two important and challenging problems in this dissertation, i.e. localization and 3D reconstruction. Specifically, most GPS based localization systems are not very accurate and can have problems in areas where no GPS signals are available. Based on the Received Signal Strength Indication (RSSI) and Inertial Navigation System (INS), we propose a new hybrid localization system, which is very efficient and can account for dynamic communication environments. Extensive simulation results demonstrate the efficiency of the proposed localization system. Besides, 3D reconstruction is a key problem in autonomous navigation and hence very important for UVS.With the help of high-speed Internet and powerful cloud servers, the light-weight computers on the UVS can now execute computationally expensive computer vision based algorithms. We develop a 3D reconstruction scheme which employs cloud computing to perform realtime 3D reconstruction. Simulations and experiments show the efficacy and efficiency of our scheme.

URI

https://hdl.handle.net/11668/19565

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