All posts by Marc Hanheide

Two Research Seminars coming up on Tuesday (28th) and Thursday (30th)

L-CAS and LIAT are jointly organising two research seminars by visiting academics, open to anyone interested.

Dr Mario Gianni (U Plymouth): Urban Search And Rescue Robotics: An In-Field Experience

Date/Time: Tue, 28/8/2018, 11:00

Room: DCB1103

Abstract

Dr Mario Gianni

On June 2012, at Mirandola, a city of Northern Italy, hit by a tremendous earthquake, I supported the deployment of a team of humans and robots to assess damage to historical buildings and cultural artefacts located therein.

On September 1, 2016, I worked in a team which deployed two ground and three aerial robots in Amatrice, Italy, to assist the response after the 6.2-magnitude earthquake, which hit and devastated the town on August 24 2016, killing 234 people.

From these two in-field experiences, I learnt that robots have really the potentials to assist responders in searching for survivors, in rescuing victims, in providing the responders with situation awareness, in creating references of the destroyed environment, in sampling suspicious substances from sites, in reaching areas that are inaccessible for humans.

In this talk, I’m going to present the research work carried out aiming at achieving these goals.

In particular, I’ll discuss the challenges and present the proposed solutions concerning building and maintaining a persistent representation of the environment, planning safe motions and controlling multi-degree-of-freedom mobile robots.

These capabilities are paramount to prevent rescue robots to get stuck in rubble-filled environments.

Florian Lier (U Bielefeld): Tackling Reproducibility in Robotics

Date/Time: Thu, 30/8/2018, 11:00

Room: DCB1103

Florian Lier
Florian Lier

Florian will be talking about his recent works on ensuring reproducibility in robotics research, the infrastructure and systems he has developed to facilitate this. He will share some experience from building robotic systems, including his recent RoboCup@Home Pepper robot system, the winner of this year’s RoboCup@Home WorldCup in Montreal.

Research Seminar Series: Orchard Robotics 28/06/18 4pm

Orchard Robotics

  • Place: DCB1102
  • Date/Time: 28/06/2018 16:00-17:00

 

 

The Lincoln School of Computer Science and the Lincoln Centre for Autonomous Systems are hosting a team of agricultural roboticists from New Zealand.

Profile Image
Prof Bruce MacDonald

The group will be represented by Prof. Bruce MacDonald and Dr Pau Medrano-Gràcia from The University of Auckland and Prof. Mike Duke from the University of Waikato. The seminar will summarize their research partnership to create robotics technology for kiwifruit and apple orchards, with the Universities of Auckland and Waikato, New Zealand’s Plant and Food Research Institute, and New Zealand company Robotics Plus. This includes an autonomous mobile robot, a targeted pollination system for kiwifruit flowers, a four-arm harvester for kiwifruit, and a prototype apple harvester.

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
Add to my Calendar:

Abstract

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.

Research Seminar: Robot Learning with an Unknown Reward Function

We are pleased to announce an exciting seminar by Robert Pinsler (Cambridge University).  He will visit us on Wednesday, 11/4/2018 and give a talk at 2pm in INB3102.

Robot Learning with an Unknown Reward Function

Robert PinslerWhile reinforcement learning has led to promising results in robotics, defining an informative reward function often remains challenging. In this talk, I will give an overview about different reward learning approaches and how they can be used for learning robotics policies in practice. In particular, I will present an efficient hierarchical reinforcement learning approach for learning how to grasp objects from preferences. Furthermore, I will show how inverse reinforcement learning can be used to learn flocking behavior of birds, which could potentially be used for apprenticeship learning of robot swarms.