PhD studentship: Advanced Aerial Robotics

The project:

We are interested in the design, perception, and control of aerial robots to foster sustainable operations. Our work is focussed on aerial-physical interactions in problems such as environmental sensing and aerial repair, and we take a nature-inspired approach to adaptive designs, algorithms, and strategies that are tailored for diverse aerial robots and tasks. We intend to address the intricate challenges posed by dynamic aerial system operations and their environments through continual learning in control design.

Themes:

Making Aerial Robotics More Functional: Enhancing the capability of aerial robots to operate in challenging environments beyond the laboratory settings with onboard localisation and path planning.

Environmental Interactivity: Designing mechanisms for aerial robots to perch, sense, and physically interact with natural structures such as trees, branches, and leaves.

Sensory Technologies for Environment: Utilizing advanced sensor technologies like cameras, lidar, and thermal/hyperspectral imaging for the detection of tree and leaf diseases.

Machine Learning for Environmental Analysis: Applying machine learning models to detect, segment, and analyse forest pathogens, identify tree phenology, and map forest areas.

Functional Aerial Robots for Natural Environments: Employing online and continual learning for developing more robust and adaptive controllers for tasks like perching, agile flight, and physical sample collection.

How to apply:

To apply for this studentship, submit a PhD application using our online application system [www.bristol.ac.uk/pg-howtoapply]

Please send your application materials to b.kocer@bristol.ac.uk with the subject line "PhD Application: Advanced Aerial Robotics".

Please ensure that in the Funding section you tick “I would like to be considered for a funding award from the School of Civil, Aerospace, and Design Engineering” and specify the title of the scholarship in the “other” box below with the name of the supervisor.

Candidate requirements: 

Applicants must hold/achieve a minimum of a master’s degree (or international equivalent) in a science, mathematics, or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree. 

• Interest in programming languages such as ROS, Python or C++.
• Interest in robot simulation environments and hands-on applications with aerial robots.
• Previous research experience in at least one of the following areas: Aerial Robotics, Design, Control Systems, Computer Vision, Machine Learning.
• Exceptional communication skills, with the ability to lead and collaborate within a research team.
• Excellent written and spoken English skills.

If English is not your first language, you need to meet this profile level:

Profile E

Further information about English language requirements and profile levels.

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