Where: online on Zoom
Time: 1:30 pm
Fourth Seminar of the PI Stories
Sara Bernardini, Royal Holloway University of London
In this talk, I will present my research on AI and Robotics for Extreme Environments.
In particular, I will discuss the open problems and research opportunities that I have identified through my work on three projects funded by Innovate UK within the program “Robotics and AI: Inspect, Maintain and Repair in Extreme Environments”. The MIMRee project concerns the construction of the first fully autonomous multi-robot platform for the inspection, maintenance and repair of off-shore wind turbines; Connect-R is about self-building modular robots for nuclear decommissioning; and Prometheus regards fully autonomous reconfigurable robots for geotechnical surveys in unknown voids. Although these projects target different domains and have different final goals, they share a common set of challenges that need to be overcome to bring AI and robotics to full fruition in real-world, sophisticated missions in challenging settings.
You will learn about those challenges and how you can contribute to tackling them.
Free participation upon registration online. The registration form will be available soon.
Register in advance for this meeting. After registering, you will receive a confirmation email containing information about joining the meeting.
About the speaker
Sara Bernardini is a professor of Artificial Intelligence at Royal Holloway University of London.
Her research focuses on designing and engineering intelligent and autonomous systems for complex, real-world applications and lie at the intersection between different areas: AI, advanced robotics and mathematical optimisation.
She has extensive experience in designing and building cutting-edge AI technology for extreme environments, and she has worked in several domains within this area such as space mission operations, nuclear decommissioning, mining and offshore energy.
Prof Bernardini is currently a co-PI of three ambitious, large projects funded by industry and the UK’s Innovation Agency: Connect-R (self-building modular robots for nuclear decommissioning); MIMRee (first fully autonomous multi-robot platform for the inspection, maintenance and repair of off-shore wind turbines); and Prometheus (fully autonomous robots for geotechnical surveys in unknown voids).
She also leads a Leverhulme grant on using game theory for large-scale, hybrid, decision-making problems.
She is a co-PI of the project Net Zero Oceanographic Capability (NZOC) funded by NERC and of the project SMaILE (Simple Methods in AI Learning and Education) funded by Fondazione Compagnia di San Paolo.
Prof Bernardini’s research has been regularly published in top-ranked AI and robotics journals and conferences, such as Artificial Intelligence Journal (AIJ), Journal of Artificial Intelligence Research (JAIR), ACM Transactions on Computer-Human Interaction (TOCHI), IEEE Robotics and Automation Letters (RA-L), AAAI Conference on Artificial Intelligence, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and International Conference on Automated Planning and Scheduling (ICAPS).
Her paper ‘Through the Lens of Sequence Submodularity’ received the ICAPS-2020 Best Paper Honorable Mention Award. Prof Bernardini will be the Program co-Chair of ICAPS-2022, and she was the Application Track co-Chair at ICAPS-2020 and the General Chair of the 3rd Summer School in Cognitive Robotics.
Contact: iecs.school [at] unitn.it
PI Stories. A series of seminars aimed at providing the opportunity to the PhD students to learn the success stories of some of the most talented researchers in the world. Each speaker will present a research project he/she led as a principal investigator. The presentation will cover the scientific scope of the project and the most important results the project achieved. The speakers will also share their own experience of turning a research idea into a successful project winning a competitive grant.
Last story on 9 June 2021: Xavier Alameda-Pineda (Université Grenoble-Alpes)