PhD Studentship: Optimal cue integration in biomimetic navigation algorithms

University of Sussex - School of Life Sciences & School of Engineering and Informatics

A Ph.D. studentship (42 months) is available from September 2018 under the supervision of Dr Paul Graham, School of Life Sciences and Prof Andrew Philippides, School of Engineering and Informatics

Navigation is a vital task for animals and robots and efficient navigation requires robustness to environmental and sensory uncertainty, with flexibility to integrate multiple sources of information. The behaviour of navigation specialists such as ants and bees, shows that they can solve these problems despite limited neural resources. A deeper understanding of the neural and theoretical basis for cue integration and robustness to sensory uncertainty would be a major benefit to the field of bioinspired navigation, where insects are templates for low-computation, low-power robots, capable of prolonged autonomy.

The basic approach will be to benchmark biomimetic models of insect navigation against navigation models from robotics. In engineering approaches to robot navigation, a family of algorithms called SLAM (Simultaneous Localisation and Mapping) provide optimal cue integration in the building of spatial representations. This optimality depends on reliable extraction of visual information and accurate information about sensor uncertainty. For this project we propose an exploration of the conditions under which biomimetic controllers approximate the performance of SLAM models. The outcomes will be improved navigation controllers for low-computation robots, and deeper understanding of how robust vision and cue integration can be implemented in neural circuits.

This exciting interdisciplinary project will form part of the EPSRC funded Brains on Board (BoB) program grant, a multi-university project in which we aim to create robots with the learning abilities of bees. You will join the Sussex BoB team and contribute to the vision of the project, while benefitting from years of experience in bio-inspired algorithms as well as cutting-edge facilities and equipment.

To excel in this project you will have either a strong quantitative background with interest in bio-inspired solutions or a biological background with strong maths and computing skills and a keen desire to improve them.

This project is one of a number ear-marked for funding by the University of Sussex Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.

Please submit a formal application using our online application system at http://www.sussex.ac.uk/study/phd/apply, including a CV, degree transcripts and certificates, statement of interest (clearly stating supervisor’s name and the project title) and names of two academic referees. On the application system use Programme of Study – PhD Biology.

Applicants will have an excellent academic record and should have received or be expected to receive a relevant first or upper-second class honours degree. The EPSRC award is available to UK and to EU students who have been ordinarily resident in the UK for the previous 3 years.  EU candidates who do not meet this criteria will be eligible for a fee waiver only. Overseas (non EU) students are not eligible to apply for EPSRC funding, but they are welcome to apply if they have access to other sources of funding.

Contact Anna Izykowska for application enquiries (a.izykowska@sussex.ac.uk).

Contact Dr Paul Graham (p.r.graham@sussex.ac.uk) or enquiries about the project.

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Type / Role:

PhD

Location(s):

South East England