In recent years unmanned aircraft systems (UAS) have been successfully used in a wide variety of applications. Their value as surveillance platforms has been proven repeatedly in both military and civilian domains. As substitutes to human inhabited aircraft, they fulfill missions that are dull, dirty and dangerous. Representative examples of successful use of UAS are in areas including battlefield assessment, reconnaissance, port security, wildlife protection, wildfire detection, search and rescue missions, border security, resource exploration and oil spill detection. The reliance of almost every UAS application on the ability to sense, detect, see and avoid from a distance has motivated this thesis, attempting to further investigate this issue.
In particular, among the various types of UAS, small scale unmanned rotorcraft or Vertically Take-off and Landing, (VTOL) vehicles have been chosen to serve as the sensor carrier platforms because of their operational flexibility. In this work we address the problem of object identification and tracking in a largely unknown dynamic environment under the additional constraint of real-time operation and limited computational power. In brief, the scope of this thesis can be stated as follows: Design a vision system for a small autonomous helicopter that will be able to: Identify arbitrary objects using a minimal description model and a-priori knowledge; Track objects of interest; Operate in real-time; Operate in a largely unknown, dynamically changing, outdoors environment under the following constraints: Limited processing power and payload; Low cost, off-the-shelf components. The main design directives remain that of real-time execution and low price, high availability components.
It is in a sense an investigation for the minimum required hardware and algorithmic complexity to accomplish the desired tasks. After development, the system was evaluated as to its suitability in an array of applications. The ones that were chosen for that purpose were: Detection of semi-concealed objects; Detection of a group of ground robots; Traffic monitoring. Adequate performance was demonstrated in all of the above cases.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-3047 |
| Date | 01 June 2009 |
| Creators | Kontitsis, Michail |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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