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  Dynamic modelling and control of a novel bio-inspired UAV for infrastructure monitoring


   School of Science, Engineering and Environment

  Prof Mary He, Dr Yunus Govdeli, Prof Osman Beg, Dr Omar Ariff  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Information on this PhD research area can be found further down this page under the details about the Widening Participation Scholarship given immediately below.

Applications for this PhD research are welcomed from anyone worldwide but there is an opportunity for UK candidates (or eligible for UK fees) to apply for a widening participation scholarship.

Widening Participation Scholarship: Any UK candidates (or eligible for UK fees) is invited to apply. Our scholarships seek to increase participation from groups currently under-represented within research. A priority will be given to students that meet the widening participation criteria and to graduates of the University of Salford. For more information about widening participation, follow this link: https://www.salford.ac.uk/postgraduate-research/fees. [Scroll down the page until you reach the heading “PhD widening participation scholarships”.] Please note: we accept applications all year but the deadline for applying for the widening participation scholarships in 2024 is 28th March 2024. All candidates who wish to apply for the MPhil or PhD widening participation scholarship will first need to apply for and be accepted onto a research degree programme. As long as you have submitted your completed application for September/October 2024 intake by 28 February 2024 and you qualify for UK fees, you will be sent a very short scholarship application. This form must be returned by 28 March 2024. Applications received after this date must either wait until the next round or opt for the self-funded PhD route.

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Project description: Inspection and maintenance of energy infrastructure such as oil pipelines, wind energy turbines or oil rigs carry a vital role in the future of the energy industry. Depending on the location of the infrastructure and the maintenance required, this could be a dangerous, tedious, and costly affair for human operators. Besides, extended downtimes pose a significant financial challenge. In this context, mobile semi-autonomous aerial robots with sensory equipment onboard provide a promising alternative as they require less human intervention and shorter maintenance periods. However, conventional winged or multirotor UAVs have endurance, size, manoeuvrability, and efficiency limitations. Bioinspiration has significant potential to improve the capabilities of already available robotic inspection systems. In this interdisciplinary project, we will investigate various dynamic modelling and control strategies of UAVs inspired by nature for an improved infrastructure monitoring mission.

In the first stage of the project, the PhD candidate will make an in-depth review of the state-of-the-art infrastructure monitoring tools and vehicles, focusing on the latest needs of the industry. Next, the Candidate will study the dynamic modelling and control of bio-inspired vehicles, which will be the core research subject of this PhD study. At this stage, the Candidate - with the supervisor’s assistance - will determine the significant design and actuation parameters inspired by nature for an efficient monitoring task. Finally, at the implementation stage, the Candidate will have the chance to fabricate their vehicle and test their findings on a series of real-time experiments.

The fundamental contributions of this work will be in the cross-section of both bio-inspired vehicle design and robotic implementation. Expected contributions would be but not limited to:

(i) The design of a novel bio-inspired aerial robotic platform.

(ii) An optimal or model-free controller application for the flight control problem.

(iii) real-time infrastructure monitoring with the designed platform and controller.

Essential skills:

"Applicants should have a bachelor’s degree (2:1 and above) and/or a Master's degree in Robotics, AI, Automation or a related STEM discipline and are interested in the proposed research. Applicants with equivalent industry experience may also apply."

Desired skills:

Experience in dynamic modelling and control of aerial or mobile robotics systems.

Experience in MAVLink – ROS communication between off-board and multirotor/winged system computers.

Experience in either Gazebo, AirSim or any other flight simulation environment.

Experience with open-source flight control firmware PX4 or ArduPilot.

Engineering (12) Medicine (26)

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