Keynote Speaker
Shane Xie
Biography: Prof Shane (Sheng Q) Xie, Ph.D., FRSNZ, FEngNZ, FIEEE, FASME, FIMechE and FAAIA, is the Chair of Robotics and Autonomous Systems and Director of the Rehabilitation Robotics Lab at the University of Leeds, and he was the Director of the Rehabilitation and Medical Robotics Centre at the University of Auckland, New Zealand (NZ, 2002-2016). He has >30 years of research experience in healthcare robotics and exoskeletons. He has published > 500 refereed papers and 8 books in rehabilitation exoskeleton design and control, neuromuscular modelling, and advanced human-robot interaction. He has supervised >15 postdocs, 100 PhDs and 80 MEs in his team with funding of >£30M from five countries since 2003. His team has invented three award-winning rehabilitation exoskeletons. He is an expert in control of exoskeletons, i.e. impedance control, adaptive control, sliding mode control, and iterative learning control strategies. He has received many distinguished awards including the New Zealand Science Challenge Award, the David Bensted Fellowship Award, and the AMP Invention Award. He is an elected Fellow of Royal Society of New Zealand, Fellow of Engineering New Zealand, Fellow of IEEE, ASME, IMechE and AAIA. He was the Technical Editor for IEEE/ASME Transaction on Mechatronics, Associate Editor for Mechatronics Elservier and Editorial member of many top journals in Mechatronics and Robotics.
Speech Information
Title: Advanced Robotics for Effective Stroke Rehabilitation Treatment in Home Environment
Abstract: Stroke and neurological diseases have significant impact on our society, robotic technologies have shown potential for delivering effective care and presented many opportunities for the healthcare industry. The talk will cover the recent development of robotics for stroke rehabilitation, the research gaps and the need for new technologies in neuroscience, robotics and artificial intelligence. The talk will introduce a EPSRC-funded project on intelligent reconfigurable exoskeletons tailored to meet patients’ needs, deliver effective diagnosis and personalised treatment, and monitored remotely by rehabilitation therapists. Examples of some of the current ongoing research work at the Leeds Centre for Assistive/Rehabilitation Robotics will be presented including peanumatic Peano muscle, DEA, soft exoskeleton, bilaterial robot, neuromuscular and brain computer interfaces. The focus is on the enabling technologies for those whose strength and coordination have been affected by amputation, stroke, spinal cord injury, cerebral palsy and ageing.
Speaker: Shane Xie, Professor
Affiliations: University of Leeds, UK
Speaker: Alessandro Di Nuovo, Professor
Affiliations: Sheffield Hallam University, UK
Alessandro Di Nuovo
Biography: Alessandro Di Nuovo is Professor of Machine Intelligence at the Department of Computing, Sheffield Hallam University (SHU). He received the Laurea (M.Sc.Eng.) and Ph.D. degrees in Informatics Engineering from the University of Catania, Italy, in 2005 and 2009, respectively. From 2012 to 2015, he was a Research Fellow with the University of Plymouth, U.K.
Prof. Di nuovo is the leader of AI, Robotics and Digital for the SHU Advanced Wellbeing Research Institute. He is the founder and leader of the Smart Interactive Technologies (SIT) Research Laboratory, which has cutting-edge facilities and equipment for conducting internationally renowned research in interdisciplinary applications of machine intelligence, including healthcare and well-being. Prof. Di Nuovo research endeavours have been supported with over £3 million by various funders to conduct ground-breaking research on interdisciplinary projects, and maintain a worldwide network of multidisciplinary scientific and industrial collaborators. Currently, he is the scientific coordinator of the Horizon Europe project “Performance in Robots Interaction via Mental Imagery” (PRIMI), which was awarded €7.3 million for 50 months, from 2023-2027.
Since 2021, he is serving as Topic Editor-in-Chief of the International Journal of Advanced Robotic Systems (Sage). He is also serving as Associate Editor for the IEEE Journal of Translational Engineering in Health & Medicine, Applied Sciences and Robotics journals (MDPI). For his academic and professional service, including organisation committees of large international conferences, he was awarded the status of Senior Member of the IEEE.
Speech Information
Abstract: Recent technological advancements have fuelled the growth of artificial intelligence (AI), making it increasingly accessible for real-world applications. Bio-inspired robotic platforms offer innovative ways to develop AI services that benefit society. These robots provide a physical embodiment that plays a critical role in cognitive processes, enabling the creation of intelligent, autonomous agents with enhanced social capabilities. An emerging field in this domain is Neuro-Robotics, which integrates computational intelligence, neuroscience, and robotics to develop artificial models of minds with human-like learning abilities rooted in biological cognition. Multidisciplinary research in health and well-being has demonstrated that advanced robots can deliver personalized assistance to individuals, such as children with autism or older adults experiencing cognitive decline, while simultaneously supporting caregivers. This talk will present the latest research findings and offer an overview of the current state-of-the-art in social robotics. It will explore the benefits, limitations, and potential breakthroughs of this technology, with a focus on conducting responsible research that empowers people rather than replacing them.
Ivan Petrović
Biography: Ivan Petrović is a full professor at the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia, where he heads the Laboratory for Autonomous Systems and Mobile Robotics – LAMOR (http://lamor.fer.hr). He is also co-director of the National Center of Research Excellence for Data Science and Advanced Cooperative Systems. His research has focused on various aspects of automatic control, state estimation, and machine learning and their application in the control of complex engineering systems for about forty years, with robot and vehicle autonomy and human-robot interaction being among his major research interests over the past twenty-five years. He has published over 80 papers in scientific journals and 220 papers in proceedings of international conferences. He has actively participated as collaborator or principal investigator in about 80 research and development projects at national and EU level. The results of his research work have been implemented in several industrial products. He is an active member of national and international professional societies. Among others, he is a fellow of the Croatian Academy of Sciences and Arts, a full member of the Croatian Academy of Engineering, a council member of the International Federation of Automatic Control (IFAC), a permanent board member of the European Conference on Mobile Robots and the International Conference on Robotics in Alpe-Adria-Danube Region and a member of the Governing Board of the Intelligent Autonomous Systems (IAS) Society. He is editor-in-chief of the Elsevier journal Robotics and Autonomous Systems and the T&F journal Automatika and an associate editor of the Elsevier journal Mechatronics.
Speech Information
Title: Towards reliable long-term robot autonomy in challenging environments
Abstract: Humans are confronted daily with uncertainties arising from precarious realities. We master complex navigation when walking or driving vehicles in various challenging scenarios. We can also deal with limited and highly noisy perceptual information, e.g. in very low light conditions, in fog and in environments with non-intuitive geometries. Humans have developed strategies to perceive their environment as accurately as necessary and make the right decisions in the complex world we live in. However, autonomous robots still have a long way to go before they achieve such a level of autonomy. To this end, autonomous mobile robots need to make autonomous decisions, perform tasks safely, and navigate accurately in uncertain environments. This talk will present some of the recent research activities and achievements of the LAMOR lab. The focus will be on our recently developed algorithms for sensor fusion, localization and mapping, motion planning and human intention recognition. I will also present experimental results for all algorithms. I will conclude the talk with a short discussion on open research challenges and possible directions for future research.
Speaker: Ivan Petrović, Professor
Affiliations: University of Zagreb, Croatia
Speaker: Louis Phee, Professor
Affiliations: Nanyang Technological University, Singapore
Louis Phee
Biography: Professor Louis Phee is the Vice President (Innovation & Entrepreneurship) and the Tan Chin Tuan Centennial Professor in Mechanical Engineering at Nanyang Technological University, Singapore. He is also a Fellow of the Academy of Engineering, Singapore. He was Dean of the College of Engineering, NTU, from 2018 till 2024. Prior to his deanship, he has served 3 years as Chair of the School of Mechanical & Aerospace Engineering. He graduated from NTU with the B.Eng (Hons) and M.Eng degrees in 1996 and 1999 respectively. He obtained his PhD from Scuola Superiore Sant’Anna, Pisa, Italy in 2002 on a European Union scholarship. His research interests include Medical Robotics and Mechatronics in Medicine. He was a recipient of the prestigious National Research Foundation (NRF) Investigator Award. Professor Phee is the co-founder of 2 NTU start-ups and is an advisor and mentor to entrepreneurial faculty and students. He was awarded the Young Scientist Award (2006), the Outstanding Young Persons of Singapore Award (2007), the Nanyang Outstanding Young Alumni Award (2011), the President’s Technology Award (2012), the Nanyang Innovation and Entrepreneurship Award (2013) and the Nanyang Alumni Achievement Award (2017).
Speech Information
Abstract: “30 by 30” vision in Singapore aims to locally produce 30% of the nation’s nutritional needs by 2030, emphasizing the importance of innovative approaches to boost agricultural productivity. Vertical farming presents a sustainable solution, optimizing land use and maximizing food production in urban environments. Automation plays a pivotal role in enhancing efficiency and addressing labor shortages and high labor costs, particularly in labor-intensive tasks such as vegetable harvesting. However, existing commercial soft robotic grippers often lack the adaptability needed for precise and reliable grasping of diverse agricultural produce. Building on our team’s experience in medical robotics, where precision and gentle manipulation is essential, we transitioned to agricultural robotics, applying these principles to develop advanced systems for vertical farming. We have developed two innovative smart and soft grippers: the Grow-and-Twine Gripper and the Extendable Envelop Gripper, specifically designed for automated leafy vegetable harvesting. These grippers seamlessly integrate Fiber Bragg Grating (FBG)-based contact force sensors for real-time interaction monitoring and vision sensors for precise detection and selection of vegetables. The Grow-and-Twine Gripper adapts to various vegetable shapes and sizes, growing and twining itself around produce for a secure, gentle grip without causing damage. The Extendable Envelope Gripper uses bendable fingers and flexible sheets to increase contact area, reducing pressure for a soft touch while ensuring a firm grasp. The soft force sensors are encased in protective tubes, shielding the optical fibers from harsh environmental conditions and ensuring durability. With high sensitivity and responsiveness, these sensors provide a wide force measurement range. The automated harvesting process, including grasping, cutting, and weighing stages, was successfully demonstrated for lettuce and Chinese kale. Our results highlight the grippers’ versatility and efficiency, showcasing their ability to handle a variety of leafy vegetables commonly found in local vertical farms. This work reflects the synergy between robotics and agriculture, demonstrating how robotics can be adapted to address challenges in food production. Future efforts will focus on integrating advanced sensor fusion techniques and refining robotic systems to automate additional vertical farming tasks, such as seedling, transplanting, and packaging. These advancements pave the way toward scalable, fully automated solutions for urban agriculture, supporting Singapore’s vision for sustainable food production.
Philippe Martinet
Biography: Philippe Martinet graduated from the CUST, Clermont- Ferrand, France, in 1985 and received the Ph.D. degree in electronics science from the Blaise Pascal University, France, in 1987. From 1990 to 2000, he was assistant Professor with CUST. From 2000 until 2011, he has been a Professor with Institut Franc ̧ais de Mécanique Avancée (IFMA), Clermont-Ferrand. In 2006, he was a visiting professor at the Sungkyunkwan university in Suwon, South Korea. In September 2011, he moves to Ecole Centrale de Nantes and LS2N. In November 2017, he moves to Inria Sophia Antipolis as Research director. His research interests include visual servoing of robots, multi-sensor-based control, force vision coupling, autonomous guided vehicles, modeling, identification and control of complex machines. He was the corresponding Chair for the RAS-TC on AGV & ITS (2012-2022), and has organized a lot of international workshops in the field of autonomous vehicles and AGV. From 1990, he is author and coauthor of around four hundred references.
Speech Information
Title: TBA
Abstract: TBA
Speaker: Philippe Martinet, Research Director
Affiliations: Inria Center at Côte d'Azur University, France