Getting to know your CDT technicians

Getting to know your CDT technicians

One of the many benefits of the AgriFoRwArdS CDT is the dedicated CDT principal engineering technicians that are located at the University of Lincoln and…

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Dr Tom Krajnik to give a talk at a world-leading AI lab in America

Dr Tom Krajnik to give a talk at a world-leading AI lab in America

A School of Computer Science STRANDS postdoc has been invited to give a presentation at a world-leading Computer Science and Artificial Intelligence Lab in the USA. Dr Tomas Krajnik, in L-CAS will give a talk next week at MIT: Computer Science and Artificial Intelligence Laboratory in Cambridge, USA on ‘FreMEn: Frequency Map Enhancement for Long-Term Autonomy of Mobile Robots’. … Continue reading Postdoc to give a talk at a world-leading AI lab in America

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STRANDS Summer School on Long-term Autonomy for Mobile Robots

STRANDS Summer School on Long-term Autonomy for Mobile Robots

From 27th August to 31st August 2015, the STRANDS project organised the first “Summer School on Long-term Autonomy for Mobile Robots” (LAMoR) at the University of Lincoln, UK; co-located with the European Conference on Mobile Robots. 25 participants fr…

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Fully-funded PhD scholarship for a UK/EU Student in Robotics

Fully-funded PhD scholarship for a UK/EU Student in Robotics

We have tentatively secured funding for an exciting PhD position (for UK/EU students only I’m afraid) in the area of Robotics. The successful candidate will be pursuing a PhD within the Lincoln Centre for Autonomous Systems (L-CAS) under the supervision of Dr Marc Hanheide and Prof Tom Duckett. The project is about long-term adaptation in human-robot collaboration for manufacturing applications
The studentship covers all fees, plus a stipend of £15000 per year for a duration of 3.5 years. The position is part of a recent strategic investment by the University of Lincoln, and only projects that recruit strong candidates will actually be funded. So, we need excellent candidates, ideally with a strong background in AI, Robotics, Mathematics, Engineering, or Machine Learning, to apply for this position to turn this funding opportunity into a real project. 
If you are excited about human-robot collaboration and its potential to change the way we manufacture, apply by sending a covering letter outlining your interest and proposed approach (up to 1 page A4) with an accompanying CV to mhanheide@lincoln.ac.uk by close of day on 18th April 2014
More details below (download the official advert here):
PROJECT DETAILS

Project Title

Facilitating Individualised Collaboration with Robots (FInCoR)

Project Reference

RIF2014S-45

Project Summary

A PhD position is available in the Lincoln Centre for Autonomous Systems Research (L-CAS), a thriving research centre based at the University of Lincoln.

L-CAS is internationally recognised for its applied autonomous systems research, in domains such as manufacturing, agriculture, security, and care. It specialises in the integration of perception, learning, decision-making and control capabilities in autonomous systems such as mobile robots and smart devices.

The Centre benefits from new, modern laboratory facilities, access to state-of-the-art robotic hardware, and offers the successful candidate a strong embedding into existing international research projects with the potential to liaise with highly regarded experts in the field. The candidate will be part of an international and ambitious team, and will benefit from excellent support to produce and disseminate original research contributions.

The PhD position is offered in the area of long-term adaptation and learning for human-robot collaboration. The project will bring together aspects of machine learning, AI and human-robot interaction, all with strong links to real-world application in manufacturing and care.

The successful applicant will be an excellent student with a very good Bachelors or Masters in Computer Science, Electronic Engineering, Mathematics or Physics who is excited about robots and can evidence relevant coding skills (C++/Python/Java/ROS). A background in machine learning, robotics, and/or AI is desirable. The project start date is 1st September 2014.

The FInCoR project will investigate novel ways to facilitate individualised human-robot collaboration through long-term adaptation on the level of joint tasks. This will enable robots to work with human more effectively in scenario such as high value manufacturing and assistive care.

Imagine a robot helping to assemble a car’s dashboard more effectively, knowing that it is working with a left-handed person; or a robot assisting an elderly employee in a car factory who is skilled in fitting a speedometer, but requires a third-hand holding the heavy mounting frame in place. Despite significant progress in human-robot collaboration, today’s robotic systems still lack the ability to adjust to an individual’s needs.

FInCoR will overcome this limitation by developing online, in-situ adaptation, putting the “human in the loop”. It will bring together flexible task representations (eg. Markov Decision Processes), machine learning (eg. reinforcement learning), advanced robot perception (eg. body tracking), and robot control (eg. reactive planning) to make progress from pre-scripted tasks to individualised models. These models account for preferences, abilities, and limitations of each individual human through long-term adaptation. Hence, FInCoR will enable processes known from human-human collaboration, such as two colleagues working together and learning more about each other’s strengths, preferences, and strategies, to take place in human-robot teams. In particular, FInCoR sets out the following objectives:
  • to develop a long-term adaptation framework for task collaboration that is governed by learning signals based on measures of performance, comfort, and ergonomics;
  • to implement the adaptation framework in the de-facto standard for robot software “ROS” to ensure effective dissemination of results and maximise impact;
  • to generate high quality outputs from original research;
  • to explore the potential of individualised adaptation in at least two market domains: high-value manufacturing  and (assistive) care, and 
  • to validate the framework within these domains, with input from international collaboration partners.

Supervisory Team

1. Dr Marc Hanheide, Senior Lecturer, School of Computer Science. http://staff.lincoln.ac.uk/mhanheide

2. Prof Tom Duckett, Professor of Computer Sciences, School of Computer Sciences. http://staff.lincoln.ac.uk/tduckett

Informal Enquiries

For further information on this project please contact Dr Marc Hanheide by email at: mhanheide@lincoln.ac.uk

Eligibility

All Candidates must satisfy the University’s minimum doctoral entry criteria for studentships of an honours degree at Upper Second Class (2:1) or an appropriate Masters degree or equivalent. A minimum IELTS (Academic) score of 7 (or equivalent) is essential for candidates for whom English is not their first language. Funded Studentships are open to both UK/EU students unless otherwise specified.

How to Apply

Please send a covering letter outlining your interest and proposed approach (up to 1 page A4) with an accompanying CV to mhanheide@lincoln.ac.uk by close of day on 18th April 2014.

Candidates will be notified w/c 5th May of the outcome of the process and if invited to interview, these are anticipated to take place w/c 26h May.

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IAS Workshop on Recent Advances in Agricultural Robotics

IAS Workshop on Recent Advances in Agricultural Robotics

My colleagues of L-CAS are organising an IAS Workshop on Recent Advances in Agricultural Robotics in lovely Padova, Italy.  If you are into growing and breeding, and want robots to help you, this is for you.

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