MSc by Research - Real-time Visual Sensing for Mobile Robotics Applications, Cranfield University

Dr Toby Breckon
Applied Mathematics and Computing Group
School of Engineering
Cranfield University
Whittle Building
Cranfield Campus
MK43 0AL

E: toby.breckon@cranfield.ac.uk

Applications are invited to participate in the ongoing applied image processing and computer vision programme over a range of different project opportunities.

The Applied Mathematics and Computing Group (AMAC) is part of the School of Engineering at Cranfield University. It specialises in the application of mathematical and computational techniques to engineering problems - including the domain of applied image and signal processing.

Applications are invited to participate in the ongoing programme of robotic sensing research work concentrated on the real-time use of image-based visual sensing for navigation and environment understanding.

The Applied Mathematics and Computing Group (AMAC) is part of the School of Engineering at Cranfield University. It specialises in the application of mathematical and computational techniques to engineering problems - including the domain of applied image and signal processing.

AMAC has been involved in image processing activities for ~20 years. Prior projects include real-time night-vision systems for major automotive manufacturers, pan-European driver monitoring/awareness projects together with a range of medical vision and security surveillance work. Recent work includes 3D computer vision for object recognition and inspection, automated ground robot and aerial target detection (MOD Grand Challenge Winners 2008, Stellar Team), airport baggage security screening and on-going automotive computer vision using low-cost on-board sensors. In general we are concerned with the novel application of image processing and computer vision approaches for the effective extraction of visual information from images.

Specific project opportunities are currently available, but not limited to, the following application domains:

• Real-time Self Localization and Mapping (SLAM) approaches for mobile robot navigation
• Thermal image understanding in complex environments from mobile robot platforms
• Real-time analysis of UAV aerial imagery for environment understanding and target detection
• Road scene understanding for intelligent robotics and driver assistance systems

Prior work of the group is available from this demos page.

Several positions available and strong applicants will be considered at any time for ongoing recruitment.

Entry Requirements

Applicants should have good background in computer science, artificial intelligence, electrical engineering or a related discipline with a strong programming ability in a high level language (preferably C/C++, Java or Matlab). Candidates should hold at least a 2:1 honours degree or equivalent in Computer Science, Electrical Engineering or a related  discipline. Applicants with industrial experience or those seeking part-time employer-sponsored study similarly welcomed.

Funding

Funded studentships to cover UK/EU fees for a 1-year MSc by Research are available for suitable qualifying applicants. Overseas applicants (non-EU) are welcome to apply for this programme of study but please note that studentships are only available for UK/EU students.

How to apply

Applicants can make initial informal enquiries with Dr. Toby Breckon. If you meet the entry requirements please make an application via the university applications page (please specify - Project title: Real-time Visual Sensing for Mobile Robotic Applications, Supervisor: Dr. Toby Breckon, Cranfield Campus)