Michael Shiel | MPhil Candidate | School of Engineering Systems
Faculty of Built Environment and Engineering | Queensland University of Technology
Gardens Point, S Block 1107 | 2 George Street, Brisbane, QLD 4000
phone: + 61 423 412 801 | email: email@example.com
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Michael holds a Bachelor of Engineering (Computer Systems) from the University of Queensland, awarded in November 2009. For his thesis Michael took part in a group effort to develop an unmanned aerial vehicle (UAV) to compete in the UAV Outback Challenge ( http://www.uavoutbackchallenge.com.au) where he simultaneously developed an infrared imaging system to locate the target, and an inertial navigation system to provide the aircraft with information about the current situation. Michael is currently undertaking a Masters degree at the Queensland University of Technology to research various methods to provide more robust and accurate situational awareness to robotic platforms, while using lower cost sensors.
Multi-level information fusion for environment aware robotic navigation
Current robotic platforms rely on relatively simple combinations of sensors to obtain information about their environment. These sensors include types such as gyroscopes, accelerometers and magnetometers. Feeding the data from these sensors through a ¿ltering algorithm enables them to be used to determine the attitude of the vehicle. Usually these ¿ltering algorithms are combined with a Global Navigation Satellite System, typically GPS, to allow them to also provide an estimate of the systems current position.
While these techniques have been heavily used and ¿eld proven, they typically have large requirements in size, weight and power, due to the devices used to provide the sensor readings. As well as this they are sensitive to their environment and most important of all, have a high cost-to-performance ratio. My research aims to address all of these issues simultaneously by both taking advantage of recent developments in the ¿eld of micro-electro-mechanical systems (MEMS) devices, and drawing cues from biological systems of a similar nature.
Work / Interests
The current platform for Michael's research is a scale model Robin 2160 RC aircraft.
Michael is also interested in expanding current control and feedback methods for CNC Machines, and has simulated and built a JGRO model CNC Mill.
Michael is working on an experimental ground control system (GCS) for UAVs written in HTML5 which utilises advanced HTML5 features such as Canvas elements for drawing, and WebSockets for data communications. This facilitates the usage of a common code base on a multitude of devices, such as mobile phones and tablet computers.