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Keynote Lectures

Robot AI and Human Safety
Angel P. Del Pobil, Universitat Jaume I, Spain

Robot Manipulation and Control
Bruno Siciliano, University of Naples Federico II, Italy

Simulation: What Made us Intelligent Will Make our Robots Intelligent
Antonio Loquercio, University of Pennsylvania, United States

 

Robot AI and Human Safety

Angel P. Del Pobil
Universitat Jaume I
Spain
http://robot.act.uji.es/lab/people/pobil/
 

Brief Bio
Angel Pasqual del Pobil is a Full Professor of Computer Science and Artificial Intelligence at Jaume I University (Spain), where he is the founding director of the UJI Robotic Intelligence Laboratory. He was a Visiting Professor at Sungkyungkwan University, Korea (2009-2021). He holds a B.S. in Physics and a Ph.D. in Industrial Engineering, both from the University of Navarra. He has been Co-Chair of two Technical Committees of the IEEE Robotics and Automation Society and is a member of the Governing Board of the Intelligent Autonomous Systems (IAS) Society (2012-present) and EURON (European Robotics Research Network of Excellence, 2001-2012). He has over 330 publications, including 14 books, three of them published by Springer: Robot Physical Interaction through the combination of Vision, Tactile and Force Feedback, Robust motion detection in real-life scenarios, and The Visual Neuroscience of Robotic Grasping. Prof. del Pobil was co-organizer of over 50 workshops and tutorials in major conferences in robotics and AI. He was Program Co-Chair of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence, General Chair of five editions of the International Conference on Artificial Intelligence and Soft Computing and General Chair of the International Conference on Simulation of Adaptive Behaviour. He is often Associate Editor for IEEE ICRA, IROS, RO-MAN, and ICDL conferences and has served on the program committees of over 240 international conferences, such as IJCAI, ICPR, ICRA, IROS, IAS, ICAR, etc. 

Prof. del Pobi award-winning research in the last 33 years, includes contributions to  humanoid robots, service robotics, internet robots, motion planning, mobile manipulation, visually-guided grasping, robot perception, robot physical and human interaction, robot learning, developmental robotics, and the interplay between neurobiology and robotics. He was a Distinguished Lecturer of the IEEE Robotics and Automation Society (2019-2024) and has presented 80 invited lectures at events around the world.


Abstract
Responsible AI is nowadays a major concern for researchers and paractitioners in the field. In particular, embodied AI in robotic systems is by its own nature prone to catastrophic risks in terms of physical damage to property, personal injury, or even death.  I will present the nature of these risks in the context of state-of-the-art robotic intelligence and the present dominant paradigm in AI, drawing some conclusions based on results from our lab.



 

 

Robot Manipulation and Control

Bruno Siciliano
University of Naples Federico II
Italy
http://wpage.unina.it/sicilian
 

Brief Bio

Bruno Siciliano is professor of robotics and control at the University of Naples Federico II. He is also Honorary Professor at the University of Óbuda where he holds the Kálmán Chair. His research interests in robotics include manipulation and control, human–robot cooperation, and service robotics. Fellow of the scientific societies IEEE, ASME, IFAC, he has received numerous international prizes and awards, including the recent 2024 IEEE RAS Pioneer Award in Robotics and Automation. He was President of the IEEE Robotics and Automation Society from 2008 to 2009. He has delivered more than 150 keynotes and has published more than 300 papers and 7 books. His book “Robotics” is among the most adopted academic texts worldwide, while his edited volume “Springer Handbook of Robotics” has received the highest recognition for scientific publishing: the 2008 PROSE Award for Excellence in Physical Sciences & Mathematics. His team has received more than 25 million Euro funding in the last 18 years from competitive European research projects, including two ERC grants. More details are available at http://wpage.unina.it/sicilian/

 


Abstract
This talk presents research results @ PRISMA Lab on robot manipulation and control. The talk is organized in four parts. In the first part, control techniques for dynamic nonprehensile manipulation are presented. The second part of the talk focuses on how to merge learning and model-based strategies to provide autonomy to robot manipulation. In the third part, several aerial robotics applications for inspection and maintenance are surveyed. The fourth part of the talk deals with recent advances on shared control including haptic guidance.



 

 

Simulation: What Made us Intelligent Will Make our Robots Intelligent

Antonio Loquercio
University of Pennsylvania
United States
 

Brief Bio
Antonio Loquercio (https://antonilo.github.io/) is an assistant professor at the University of Pennsylvania. He received his PhD and M.Sc. from UZH and  ETH Zurich in 2021 and 2017. His research interests include learning-based robotics, computer vision, and machine learning. His work includes seminal results on vision-based agile flight via learning sensorimotor policies and continual learning in legged locomotion. He is the recipient of the 2017 ETH Medal for Outstanding Master Thesis, the Best System Paper Award at the Conference on Robot Learning (CORL) 2018, the RSS’20 Best Paper Award Honorable Mention, and the T-RO’20 Best Paper Award Honorable Mention. His article on superhuman drone racing was featured on Nature’s cover. He received the Georges Giralt PhD Award, the most prestigious award for PhD dissertations in robotics in Europe.


Abstract
Simulation-to-reality transfer is an emerging approach that enables robots to develop skills in simulated environments before applying them in the real world. This method has catalyzed numerous advancements in robotic learning, from locomotion to agile flight. In this talk, I will explore simulation-to-reality transfer through the lens of evolutionary biology, drawing intriguing parallels with the function of the mammalian neocortex. By reframing this technique in the context of biological evolution, we can uncover novel research questions and explore how simulation-to-reality transfer can evolve from an empirically driven process to a scientific discipline.



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