Using machine learning techniques to optimise the motion performance of soft robots physically interacting with their environment

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This PhD research proposal will develop “soft” robotics in sub aqua marine environments where these are not yet as well developed as “hard” land based robotics systems. Existing “hard” robotics systems provide wide ranging capability with varying levels of autonomy (algorithms/software)

and mission systems requirements, including technologies for sensing, orientation, decision making/planning, control.

 

This project has potential to co-develop research capacity and application of this technology. Prototypes and potential use cases will provide protection and support keeping military, first responders and civilians safe. Application might cover IED defeat, CBRN/hazmat identification, reconnaissance, combat engineering support, logistics, explosive inspection and disposal, fisheries protection, the development of tactics, techniques and behaviours for Manned and Unmanned Teaming in dynamic, uncertain environments.

 

This will include development of working prototypes, modular in design, to enable integration of third-party software and easy system upgrades. Safety and the validation and verification of such systems will enhance defence capability in this area to prevent personnel being exposed to risks and hazards.

 

This PhD project is a collaboration between University Queen Mary University of London, UK and ENSTA Bretagne, France.

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How To Apply

To apply for this studentship and for entry on to the Mechanical Engineering programme (Full Time) please follow the instructions detailed on the following webpage:

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Research degrees in Engineering:

http://www.qmul.ac.uk/postgraduate/research/subjects/engineering.html

 

Further Guidance: http://www.qmul.ac.uk/postgraduate/research/

 

Please be sure to include a reference to ‘2020 SEMS KAA’ to associate your application with this studentship opportunity.

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Entry requirements

Candidates should have a first-class honours degree or equivalent, or a

good MSc Degree, in electrical or mechanical engineering, computer science, or a field closely related to robotics. Strong motivation to aim for excellence is essential. Applicants with advanced knowledge of robotics, control, machine learning, artificial intelligence, tactile sensing and/or previous research experience in these fields are particularly encouraged to apply.

 

English language requirements

If English is not your first language you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking). The test must be dated within two years of the start date of the course in order to be valid.

 

Funding on offer

This studentship is available to UK and French candidates only. It is funded by Dstl for 3 years, and it will cover student fees and a tax-free stipend of £17, 285 per annum.

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Contact details

For information regarding the project, please contact Prof Kaspar Althoefer by email: k.althoefer@qmul.ac.uk.