Tag Archives: l-cas

SoCS Seminar Series: Task Planning for Long-Term Autonomy in Mobile Service Robots

The Lincoln School of Computer Science and the Lincoln Centre for Autonomous Systems are excited to host Prof Nick Hawes (University of Oxford, Oxford Robotics Institute) in their research seminar series:

Task Planning for Long-Term Autonomy in Mobile Service Robots

Place and Time

  • Place: DCB1102
  • Date/Time: 13/7/2018 10am
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The performance of autonomous robots, i.e. robots that can make their own decisions and choose their own actions, is becoming increasingly impressive, but most of them are still constrained to labs, or controlled environments. In addition to this, these robots are typically only able to do intelligent things for a short period of time, before either crashing (physically or digitally) or running out of things to do. In order to go beyond these limitations, and to deliver the kind of autonomous service robots required by society, we must conquer the challenge of combining artificial intelligence and robotics to develop systems capable of long-term autonomy in everyday environments. This talk will present recent progress in this direction, focussing on the mobile robots for security and care domains developed by the EU-funded STRANDS project (http://strands-project.eu) which have so far completed over 106 days of autonomy in real service environments. In particular the presentation will cover our approach which combines probabilistic verification and machine learning to produce a planning system which controls how the robots select and execute their tasks over these extended periods of autonomy.

Speaker bio

Nick Hawes is an Associate Professor of Engineering Science in the Oxford Robotics Institute at the University of Oxford. His research applies techniques from artificial intelligence to allow robots to perform useful tasks for, or with, humans in everyday environments (from moving goods in warehouses to supporting nursing staff in a care home). He is particularly interested in how robots can understand the world around them and how it changes over time (e.g. where objects usually appear, how people move through buildings etc.), and how robots can exploit this knowledge to perform tasks more efficiently and intelligently.

Gregory Epps to Demonstrate DogBot at Research Seminar

The Lincoln Centre for Autonomous Systems (L-CAS) and Lincoln Institute for Agri-Food Technology (LIAT) will welcome CEO of React AI, Gregory Epps, and ‘DogBot'; a quadruped robot.

Gregory will discuss the exciting new robotic platform and the research behind it as well as providing a live demonstration of DogBot.


The seminar will be on Friday 18th May 2018, 11:00am, in AAD0W25.

Everybody is welcome to join!

DogBot is a quadruped robot built for AI research, built by AI and robotics experts with an eye on the future. It breaks free from the need for heavy, slow and rigid limbs by utilising ultra-light carbon fibre and 3D printed parts to complement powerful torque controlled motors. The robot uses real-time AI control, resulting in lifelike control and motion.
React Robotics will provide a platform for academic researchers to test their control algorithms in the real world. We are introducing the DogBot to the market at just £19,995+VAT, and we encourage you sign up to be notified when the DogBot will be available for pre-order.

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.

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


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.