Tag Archives: l-cas

University of Lincoln joins network of leading UK robotics research centres

The University of Lincoln has been added to a growing national network of the UK’s leading robotics research centres.

The Lincoln Centre for Autonomous Systems Research has joined the UK Robotics and Autonomous Systems Network (UK-RAS Network). The network was established in 2015 by the UK’s Engineering and Physical Sciences Research Council to provide academic leadership in Robotics and Autonomous Systems (RAS), expand collaboration with industry and integrate and coordinate activities between research centres.

UKRASNetwork
The UK Government has identified robotics and autonomous systems as a priority area which can help drive international competitiveness, productivity and economic growth.

The UK-RAS Network organises a wide range of activities including UK Robotics Week, networking events, focused workshops, public engagement and exhibitions. Other network member universities include Imperial College London, the University of Oxford and the University of Manchester.

The Lincoln Centre for Autonomous Systems (L-CAS) is based in the School of Computer Science at the University of Lincoln. Its researchers participate in a range of collaborative research projects with other academic and industry partners. The centre specialises in technologies for perception, learning, decision-making, control and interaction in autonomous systems, especially mobile robots and robotic manipulators, and the integration of these capabilities in sectors such as agri-food, healthcare, intelligent transportation and logistics.

Thorvald, the Agri-Food robot.
Thorvald, the Agri-Food robot.

Professor Tom Duckett, Director of L-CAS at the University of Lincoln, said: “We are very pleased to have joined the UK-RAS Network, which brings together the UK’s leading academic research centres for robotics and autonomous systems. We believe the University brings some unique specialisms to the network through our particular expertise, facilities and approach to working with industry. By nature robotics research tends to be collaborative and inter-disciplinary in scope, so the network can only help the UK emerge as a world leader in developing and exploiting these technologies.”

Major L-CAS research projects include ENRICHME, which is developing next-generation mobile service robots to help elderly people to stay independent and active for longer, and ILIAD, which will introduce fleets of autonomous ‘self-optimising’ forklift trucks which can operate safely and efficiently in warehouses alongside human co-workers. The centre also contributes to the inter-disciplinary research of the Lincoln Institute for Agri-food Technology and the Lincoln Institute for Health.

Research facilities include dedicated robotics research labs in the University’s new Isaac Newton Building, a demonstration farm at the Riseholme Campus, and an experimental food factory at the National Centre for Food Manufacturing in Holbeach.

Teams also have access to a fleet of diverse mobile and social robots, advanced compliant robotic manipulators, a swarm of micro robots, and state-of-the-art agricultural robots, including the Thorvald platform.

Article re-blogged from: http://www.lincoln.ac.uk/news/2018/01/1428.asp

 

 

Robotics Research Seminar 24/5/17: “Making Robust SLAM Solvers for Autonomous Mobile Robots”

We invite everybody to attend the robotics research seminar, organised by L-CAS, on Wednesday 24/5/2017:

grisettiDr Giorgio Grisetti, DIAG, University of Rome “Sapienza”:

Making Robust SLAM Solvers for Autonomous Mobile Robots

  • WHERE: AAD1W11, Lecture Theatre (Art, Architecture and Design Building), Brayford Pool Campus
  • WHEN: Wednesday 24th May 2017, 3:00 – 4:00 pm

ABSTRACT:

In robotics, simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent’s location within it.

SLAM is an essential enabling technology for building truly autonomous robots that can operate in an unknown environment. The last three decades have seen substantial research in the field and modern SLAM systems are able to cope easily with operating conditions that in the past were regarded as challenging if not impossible to deal with.

This consideration might support the statement that SLAM is a closed problem. However a closer look at the contributions presented in the most relevant conferences and journals in robotics reveals that the papers on SLAM are still numerous and the community is large. Would this be the case if an off-the shelf solution that works all the time were available?

Non-experts that approach the problem, or even want to get one of the state-of-the-art systems running, often encounter problems and get performances that are far from the ones reported in the papers.  This is usually because the person using the system is not the person designing the system.  An open box approach that aims at solving the problems by modifying an existing pipeline is often hard to implement due to the complexity of modern SLAM systems.

In this talk we will overview the history of SLAM and we will outline some of the challenges in designing robust SLAM systems, and most importantly forming robust SLAM solvers.

Furthermore, we will also present PRO-SLAM (SLAM from a programmer’s perspective), a simplistic open-source pipeline that competes with state-of-the art Stereo Visual SLAM systems while focusing on simplicity to support teaching.

https://gitlab.com/srrg-software/srrg_proslam

Lincoln computer science research papers accepted

Lincoln Centre for Autonomous Systems (L-CAS) submitted research papers to SAC 2017 and HRI 2017, and have been accepted.

The first paper to be presented at SAC 2017 is joint work with Dr Marc Hanheide‘s PhD student Peter Lightbody and Dr Tomas Krajnik on “A Versatile High-Performance Visual Fiducial Marker Detection System with Scalable Identity Encoding”.

Fiducial markers have a wide field of applications in robotics, ranging from external localisation of single robots or robotic swarms, over self-localisation in marker-augmented environments, to simplifying perception by tagging objects in a robot’s surrounding.

We propose a new family of circular markers allowing for a computationally efficient detection, identification and full 3D position estimation. A key concept of our system is the separation of the detection and identification steps, where the first step is based on a computationally efficient circular marker detection, and the identification step is based on an open-ended `necklace code’, which allows for a theoretically infinite number of individually identifiable markers.

The experimental evaluation of the system on a real robot indicates that while the proposed algorithm achieves similar accuracy to other state-of-the-art methods, it is faster by two orders of magnitude and it can detect markers from longer distances.

The second paper that has been accepted at HRI 2017, which has an acceptance rate of only 24%, is co-authored by Marc Hanheide, Denise Hebesberger, and Tomas Krajnik:
“The When, Where, and How: An Adaptive Robotic Info-Terminal for Care Home Residents – a long-term study”

Adapting to users’ intentions is a key requirement for autonomous robots in general, and in-care settings in particular. In this paper, a comprehensive long-term study of a mobile robot providing information services to residents, visitors, and staff of a care home is presented with a focus on adapting to the when and where the robot should be offering its services to best accommodate the users’ needs.

Rather than providing a fixed schedule, the presented system takes the opportunity of long-term deployment to explore the space of possibilities of interaction while concurrently exploiting the model learned to provide better services. But in order to provide effective services to users in a care home, not only the when and where are relevant, but also the way the information is provided and accessed. Hence, also the usability of the deployed system is studied specifically, in order to provide a most comprehensive overall assessment of a robotic info-terminal implementation in a care setting.

Our results back our hypotheses, (i) that learning a spatiotemporal model of users’ intentions improves efficiency and usefulness of the system, and (ii) that the specific information sought after is indeed dependent on the location the info-terminal is offered.

This is a great achievement for our PhD students and researchers, and you can keep up to date with our L-CAS research here: https://lcas.lincoln.ac.uk/wp/ 

 

SoCS Research Seminar Series on 27/11/2015: Prof Nick Taylor (HWU)

nkt

The School of Computer Science is pleased to welcome Prof Nick Taylor (from Heriot-Watt University) for a research talk as part of the School’s research seminar series. Prof Taylor will be presenting current research from “The Edinburgh Centre for Robotics”.

 

When?

Fri 27/11/2015, 10am

Where?

David Chiddick Building, Room BL1105 (1st Floor)

Abstract:

The Edinburgh Centre for Robotics harnesses the potential of 30 world leading investigators from 12 cross-disciplinary research groups and institutes across the Schools of Engineering & Physical Sciences and Mathematical & Computer Sciences at Heriot-Watt University and the Schools of Informatics and Engineering at the University of Edinburgh. Our research focuses on the interactions amongst robots, people, environments and autonomous systems, designed and integrated for different applications, scales and modalities. We aim to apply fundamental theoretical methods to real-world problems on real robots solving pressing commercial and societal needs. The Centre offers a 4 year PhD programme through the EPSRC Centre for Doctoral Training in Robotics and Autonomous Systems and hosts the Robotarium national UK robotics facility.
http://www.edinburgh-robotics.org/
https://www.facebook.com/edinburghcentreforrobotics
@EDINrobotics

Biography

Nick Taylor is a Professor of Computer Science at Heriot-Watt University and a Deputy Director of the Edinburgh Centre for Robotics. He was Head of Computer Science from 2008-2014 and leads the Pervasive, Ubiquitous and Mobile Applications (PUMA) Lab which he formed in 2010. He has been involved in robotics and machine learning research for over three decades, most recently with a particular interest in the personalisation of autonomous systems for pervasive environments. Nick took his A-levels at Lincoln Christ’s Hospital School and then studied at Cardiff, London and Nottingham before joining Heriot-Watt University and settling in Midlothian.
http://www.hw.ac.uk/schools/mathematical-computer-sciences/staff-directory/nicholas-taylor.htm
http://www.macs.hw.ac.uk/puma/