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AI Enhanced LiDAR Perception for Autonomous Drone Systems (PHDCEPS2021003)


Computing, Engineering & Physical Sciences

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Dr J Riordan , Dr S Matalonga No more applications being accepted Funded PhD Project (European/UK Students Only)

About the Project

This PhD project will develop embedded software for unmanned aerial drones to optimise their ability to detect hazards in challenging and complex situations, such as during autonomous flight in and around large built infrastructure in urban and industrial environments.

The post is fully funded for 3 years, with fees and stipend for UK and EU eligible students.

The successful candidate will work across artificial intelligence, machine vision, perception sensor modelling, and high-performance virtual reality systems. The research objectives focus on extending the capabilities of drone sensor perception to optimise the risk management of flight beyond visual line of sight. The PhD candidate will develop innovative artificial intelligence algorithms for self-optimisation of LIDAR sensor perception, and extend virtual reality scenario simulation to enable mission profiling and hazard mitigation. The work will exploit massively parallel GPU compute frameworks for validation of sensor-driven machine vision and drone context awareness systems.

The successful candidate will have obtained a First Class or Upper Second Class honours degree or Masters in a relevant technology or engineering discipline (Robotics/Software/Electronics). Applicants are expected to demonstrate excellent technical skills in high-performance software development (preferably Python, C++, CUDA / SYCL), with particular importance given to expertise in design and development of algorithms for high performance and/or resource-constrained use cases. The ideal applicant will have some experience in cloud technologies for machine learning and artificial intelligence, especially for big data or sensor-driven applications. Knowledge and understanding of research and project management methodologies is desirable. Excellent verbal and written communication skills in English are a must.

The successful candidate will join the ALMADA Research Centre at the UWS Lanarkshire campus and will work closely with researchers on large projects within the lab. For example, the ALMADA team are leading the €5 million European Commission H2020 RAPID project (Risk Aware Port Inspection Drones), which will extend drones to autonomously monitor maritime transport infrastructures such as bridges, ports, and ships. ALMADA research partners include industry leaders Thales, SINTEF, Fraunhofer, Codeplay, Port of Hamburg, XOcean, as well as universities across the UK and Europe.

The PhD project is available for immediate start and will stay open until filled. Suitably qualified candidates will be invited to be interview shortly after on receipt of their application. Please send a CV and cover letter to the research leads Dr. James Riordan ([Email Address Removed]) and Dr. Santiago Matalonga ([Email Address Removed]).

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