Luogo: NOI Techpark, Via Volta 13, stanza A1.-1 Seminar 3 (seminario) e Sala Carroponto (apertura formale e guide laboratorio)
Registrazione: Si prega di registrare qui
|9:00||Apertura dell’ evento|
|9:15||Presentazione keynote di Andrea Zanchettin: Collaborative robotics: from safe robots to intelligent coworkers|
|10:15||Presentazione keynote di Giorgia Chalvatzaki: Shaping Robotic Assistance through Structured Robot Learning|
|11:15||Breve presentazione del laboratorio da parte di Angelika Peer|
|11:30||Apertura del laboratorio da parte di Paolo Lugli (Rector of Free University of Bolzano) e Hubert Hofer (Deputy CEO of NOI Techpark)|
|12:00||Pranzo e guide laboratorio|
Associate Professor, Politecnico di Milano
Title: Collaborative robotics: from safe robots to intelligent coworkers
This talk will overview the research activities on collaborative robotics performed in the Mechatronics and Robotics Laboratory for Innovation (MeRLIn) of Politecnico di Milano.
Several topics of this field will be introduced and discussed, ranging from safety aspects to the use of Artificial Intelligence for a better, fluent, and productive collaboration between humans and robots. The actualisation of the developed research on realistic and industry-relevant applications will be also shown.
Andrea Zanchettin was born in Cremona (Italy) in 1983. He received his MSc and PhD degree from Politecnico di Milano in 2009 and 2012, respectively.
He is presently appointed as Associate Professor in Automatic Control. His research interests are about mechatronic systems, automatic control, and intelligent human-robot collaboration.
Since 2017, Andrea Zanchettin has been co-founder and co-chair of the IEEE RAS Technical Committee on Collaborative Automation for Flexible Manufacturing (CAFM).
Prof. Zanchettin is presently serving as Chair of the Italian Chapter of the IEEE RAS (I-RAS), as well as Executive VP for Industrial Activities of the Italian Institute of Robotics and Intelligent Machines (I-RIM).
He is also co-founder and member of the Board of Directors of Smart Robots, a spin-off company of Politecnico di Milano.
Assistant Professor, TU Darmstadt, Germany
Title: Shaping Robotic Assistance through Structured Robot Learning
Future intelligent robotic assistants are expected to perform various tasks in unstructured and human-inhabited environments. These robots should support humans in everyday activities as personal assistants or collaborate with them in work environments like hospitals and warehouses. In this talk, I will briefly describe my research works for robotic assistants to help and support humans in need, developing specific human-robot interaction behaviors combining classical robotics and machine learning approaches. I will then explain how mobile manipulation robots are currently the most promising solution among embodied AI systems, thanks to their body structure and sensorial equipment for learning to execute a series of assistive tasks. On top of this, I will point out some key challenges that hinder autonomous mobile manipulation for intelligent assistance, and discuss how structured robot learning can pave the way toward generalizable robot behaviors. Structured robot learning refers to all learning methods at the intersection of classical robotics and machine learning that aim to leverage structure in data and algorithms to scale robot behaviors to complex tasks. Finally, this talk will give insights into how my team and I leverage structured representations, priors, and task descriptions together with learning and planning in some challenging (mobile) manipulation tasks in our path for creating general-purpose intelligent robotic assistants.
Georgia Chalvatzaki is Assistant Professor and research leader of the intelligent robotic systems for assistance (iROSA) group at TU Darmstadt, Germany. She received her Diploma and Ph.D. in Electrical and Computer Engineering at the National Technical University of Athens, Greece. Her research interests lie in the intersection of classical robotics and machine learning to develop behaviors for enabling mobile manipulator robots to solve complex tasks in domestic environments with the human-in-the-loop of the interaction process. She holds an Emmy Noether grant for AI Methods from the German research foundation. She is a co-chair of the IEEE RAS technical committee on Mobile Manipulation, co-chair of the IEEE RAS Women in Engineering committee, and was voted “AI-Newcomer” for 2021 by the German Information Society.