Min Pan, Professor of Intelligent Machine Systems and UKRI Future Leaders Fellow from the Department of Mechanical Engineering at the University of Bath, will lead the 2.2 million research project over 36 months to develop a new framework for modelling dexterous manipulators of soft robotic systems.
The emerging technologies for soft robotics provide flexible and compliant material for a new engineering design that creates more life-like robotic systems. This enables greater robotic flexibility, dexterous handling, and adaptability of medical devices, allowing robotics to be used in a wider range of sectors, including manufacturing, medicine, healthcare, rehabilitation, assistance and rescue.
Whilst soft robotic manipulators and systems have improved tremendously over the last decade, they continue to present complexities and challenges in their design, modelling, and control. A fundamental challenge is the lack of understanding of how the soft manipulators behave during motion. There is also no effective analytical framework for understanding the behaviours, characteristics, and dynamics of these soft robotic systems.
The University of Bath research team led by Professor Pan includes: Co-Investigator Professor Patrick Keogh, Head of Mechanical Engineering, who will advise on manipulator mechanics and dynamics; Co-Investigator Professor Chris Bowen, Associate Dean for Research in the Faculty of Engineering and Design, to advise on material properties and characteristics of soft manipulators; and Dr Cangxiong Chen, Institute for Mathematical Innovation (IMI) who brings expertise in Machine Learning and mathematics. They will work with collaborators from the University of Cambridge and spinout company MorphoAI.
Machine Learning has significant potential for understanding the complex and unpredictable behaviour of soft manipulators, and importantly for the development of a pioneering new modelling framework. This will help overcome unpredictability, ineffectiveness, and inaccuracy of the soft manipulators during motion.
Professor Min Pan says, Department of Mechanical Engineering, says:
We are thrilled about the opportunity to explore and address the fundamental research challenges related to robotic dexterity. We aim to create a new analytical framework involving new model- and learning-based approaches and their integration to open new horizons in understanding the behaviours, fundamental characteristics, dynamics, and internal physical interactions of soft manipulators. Working with the ARIA Programme Director, Professor Jenny Read, to facilitate a transition from a "Genesis paradigm" to a "Darwin paradigm" in robotics, we will optimise robot hardware - encompassing body morphology, mechanics, and material properties - alongside software elements such as manipulation, control, and decision-making, together in a process similar to evolution. Our ambitions will open new horizons in science and engineering by bringing together interdisciplinary areas of robotics, modelling, physics, and machine learning.
Professor Chris Bowen, Associate Dean for Research in the Faculty of Engineering and Design, says:
Our research directly aligns with the ARIA vision and research strategy, and Robotics will be a subject of intense research well into the future. We feel our scientific work could contribute to the creation of next-generation intelligent and dexterous machines that have the potential to revolutionise the field, generate high impacts on our economy and benefit our society.
ARIA Programme Director, Professor Jenny Read, says:
Soft, compliant and deformable materials will be increasingly important in next-generation robotics, but with traditional approaches, it's hard to predict how such materials will respond. I'm delighted to have Professor Pan and her collaborators to help us understand how best to use these materials to build robots that are safe, capable and highly dexterous.
More on the ARIA robot dexterity programme.
Dr Pan's research proposal was supported by Research and Impact Services (RIS). For support in developing your research please contact the Research Development team in RIS: resdev@bath.ac.uk.