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Vision based maneuvering for autonomous aircraft

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  • Full or part time
    Prof W Holderbaum
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

About This PhD Project

Project Description

Reference Number: PI-WH-2017-1018-1-PhD

Project Summary:
This project investigates the application of computer vision and computational neuroscience in motion control and planning for unmanned aerial vehicles (UAVs).

Specific Requirements of the Project


The potential applicants will have:
Bachelors (at least 2.1 or equivalent) or Masters Degree with Control Engineering, Electronics, Embedded Systems, Control Theory, Computing and Mathematics as major subjects.

Experience in real time control systems, programming, systems engineering and mechanical design is highly desirable

Experience in modelling, control and programming in Matlab/Simulink environment is highly desirable.

It is important to be able write publications and to present your research work to audiences from specialists to the general public.

Project Aims and Objectives


The study and development of autonomous unmanned aerial vehicles has important applications in both civilian and military areas. Military UAV’s are mainly used in used for intelligence, surveillance, reconnaissance (ISR), and strikes.

The civil market for UAV’s is constantly growing with the increased funding in Europe and the US. Current potential civilian applications of UAV’s include:
• Inspection of terrain, pipelines, utilities, buildings, etc.
• Law enforcement and security applications.
• Surveillance of coastal borders, road traffic, etc.
• Disaster and crisis management search and rescue.
• Environmental monitoring.
• Agriculture and forestry.
• Fire fighting.
• Communications relay and remote sensing.
• Aerial mapping and meteorology.

The main area of research for the student will be the integration of computer vision and computational neuroscience for controlling a planning of maneuvers of an unmanned aerial vehicle.

These control and planning strategies will allow real time decision making for obstacle avoidance for moving objects in the flight path, as well as fast planning of critical maneuvers such as landing, and interception of moving targets.

The student will perform an extensive literature review on computer vision and computational neuroscience techniques with potential to be combined with computer vision approaches for UAV (Unmanned Air Vehicle) path planning and control systems. The student will familiarize with the UAV research facilities available in the industries This will include how to embed control techniques using Matlab/Simulink into the onboard computer systems.

A number of appropriate techniques will be implemented and combined with computer vision methods. Theoretical analyses and numerical simulations will be performed. Test scenarios will be defined as well as performance measures. Experiments will be planned and the test environment, equipment and software will be prepared for experiments. It is hoped that initial flight tests will be performed and extensive experimental work with the possibility to improve the control and planning strategies, followed by a period of data analysis of. it is expected that two journal publications will have been submitted.

It is expected that two publications will be submitted during the PhD thesis.
The project impact has potential to cross many boundaries helping initially the further develop UAV control and motion planning strategies.

The project impact has potential to cross many boundaries helping initially the further develop UAV control and motion planning strategies.

Project only open to: Home/EU and overseas

Informal enquiries can be made to [Email Address Removed]


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