Tag Archives: Robotics

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.

Screenshot_Adobe_Acrobat_20180516-185510

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.

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

 

 

Research Seminar, Fr 10/11/17 2pm: Modelling and Detecting Objects for Home Robots

Everyone interested robotics, computer vision, and computer science in general is cordially invited to the School of Computer Science research seminar

on Friday, 10/11/2017 at 2pm

in room JUN0001 (The Junction).

Modelling and Detecting Objects for Home Robots

Markus Vincze, Technical University Vienna

Abstract

In the near future service robots will start to handle objects in home tasks such as clearing the floor or table, making order or setting the table. Robots will need to know about all the objects in the environment. As a start, humans could show their favourite objects to the robot for obtaining full 3D models. These models are then used for object tracking and object recognition. Since modelling all objects in a home is cumbersome, learning object classes from the Web has become an option. While network based approaches do not perform too well in open settings, using 3D models and shape for detection in a hypothesis and verification scheme renders it possible to detect many objects touching each other. Finally, the models are linked to grasp point detection and warping, so that objects with small differences can be handled and the uncertainty of modelling as well as the robot grasping are taken care of. These methods are evaluated in settings for taking objects out of boxes, to pick up objects from the floor and for keeping track of objects in user homes.

Biography of Markus Vincze

Markus-Vincze-e1504228193491Markus Vincze received his diploma in mechanical engineering from Technical University Wien (TUW) in 1988 and a M.Sc. from Rensselaer Polytechnic Institute, USA, 1990. He finished his PhD at TUW in 1993. With a grant from the Austrian Academy of Sciences he worked at HelpMate Robotics Inc. and at the Vision Laboratory of Gregory Hager at Yale University. In 2004, he obtained his habilitation in robotics. Presently he leads the “Vision for Robotics” team at TUW with the vision to make robots see. V4R regularly coordinates EU (e.g., ActIPret, robots@home, HOBBIT) and national research projects (e.g, vision@home) and contributes to research (e.g., CogX, STRANDS, Squirrel, ALOOF) and innovation projects (e.g., Redux, FloBot). With Gregory Hager he edited a book on Robust Vision for IEEE and is (co-)author of 42 peer reviewed journal articles and over 300 reviewed other publications. He was the program chair of ICRA 2013 in Karlsruhe and will organize HRI 2017 in Vienna. Markus’ special interests are cognitive computer vision techniques for robotics solutions situated in real-world environments and especially homes.

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