Dynamic modelling and control of a novel bio-inspired UAV for infrastructure monitoring
About the Project
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.
Supervisors
For more information about the School of Science, Engineering and Environment at the University of Salford visit:
Please use this Research Proposal, Personal statement, and CV GUIDE when preparing an application:
How to apply:
https://www.salford.ac.uk/school-of-science-engineering-and-environment/postgraduate-research
Funding Notes
To inquire about University of Salford funding schemes – including the Widening Participation Scholarship – visit this website:
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