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AISB Convention 2016

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AISB opportunities Bulletin Item

Studentships in Cognitive Robotics, University of Leeds, UK

2 x Studentships in Cognitive Robotics at the University of Leeds 

Project STRANDS: Spatial-Temporal Representations and Activities For Cognitive Control in Long-Term Scenarios

Two PhD studentships are available funded by a new EU grant, STRANDS: Spatial-Temporal 
Representations and Activities For Cognitive Control in Long-Term Scenarios. Leeds is a 
partner in this multi-site project, and is particularly concerned with developing appropriate 
qualitative spatio-temporal representations and with learning activity models in a long term 
temporal setting. The other partners in the consortium are the Universities of Birmingham 
(coordinating node), Lincoln, Vienna, RWTH Aachen, and  KTH Stockholm.

STRANDS aims to enable a robot to achieve robust and intelligent behaviour in human environments 
through adaptation to, and the exploitation of, long-term experience. Our approach is based on 
understanding 3D space and how it changes over time, from milliseconds to months. We will develop 
novel approaches to extract quantitative and qualitative spatio-temporal structure from sensor 
data gathered during months of autonomous operation. Extracted structure will include reoccurring 
geometric primitives, objects, people, and models of activity. We will also develop control 
mechanisms which exploit these structures to yield adaptive behaviour in highly demanding, 
real-world security and care scenarios.

The spatio-temporal dynamics presented by such scenarios (e.g. humans moving, furniture changing 
position, objects (re)appearing) are largely treated as anomalous readings by state-of-the-art 
robots. Errors introduced by these readings accumulate over the lifetime of such systems, 
preventing many of them from running for more than a few hours. By autonomously modelling 
spatio-temporal dynamics, our robots will be able run for significantly longer than current 
systems. Our systems will take these opportunities, advancing long-term mapping, life-long 
learning about objects, person tracking, human activity recognition and self-motivated behaviour 
generation. We will integrate our advances into complete cognitive systems to be deployed and 
evaluated at two end-user sites. The tasks these systems will perform are impossible without 
long-term adaptation to spatio-temporal dynamics, yet they are tasks demanded by early adopters 
of cognitive robots. 

The two studentships will start from 1/4/2013 or as soon as possible thereafter. Successful 
applicants will be paid a stipend which will be sufficient for them to pay their own fees at 
the appropriate rate, leaving sufficient left over for maintenance at the UK EPSRC rate 
(approximate 13,500 tax free ).

Candidates should have or expect to obtain a first class or good 2.1 honours degree in 
mathematics, computer science or artificial intelligence. Preference will be given to candidates 
who can offer a Masters level qualification, a track record in publications, or relevant experience.

The School of Computing is among the 10 best Computing departments in the UK according to the 2008 
Research Assessment Exercise (RAE).  An impressive 80% of staff is rated internationally excellent
or world leading. This clearly confirms the School's position as one of the leading computing 
departments in the UK and a leader in the field internationally.
Formal applications for research degree study must be made either on line through the University 
website, or on the University's application form. Detailed information of how to apply on line 
can be found at:  
The paper application form is available at:  
Please return the completed application form to the Research Degrees & Scholarships Office, 
University of Leeds, LS2 9JT.
Please note, if you intend to send academic references we can only accept them if they are on 
official letter headed paper and contain an original signature and stamp; they must arrive in 
sealed envelopes.  Alternatively, the School will contact your named academic referees directly.

Informal enquiries can be made to Prof Tony Cohn,, +44 113 343 5482