Research Workshop 13th June 2021
Talk Title
Interaction between Feedback and Artificial Intelligence in High Levels of Automation
Abstract
Driverless cars, unmanned aircraft, fully automated mining in deep ground/sea, and healthcare robots looking after elder and disabled people — these are hot words we are seeing in the media, and discussed and debated at home and pubs. There is a huge aspiration about future highly automated society. But are we ready for that? Are they safe? This talk will discuss the limits of the current control theory and the lack of understanding of the interactions between different parts involved in robotics and autonomous such as perception, decision making/planning, uncertainty, environment, and system dynamics. Quite often the role of feedback is overlooked in the high levels of functions in dealing with events and uncertainty arising in an operational environment. It argues that autonomous control theory, as opposite to current automatic control theory, shall be developed to understand the role of feedback in highly automated systems. To achieve this goal, a close collaboration with computer science (e.g. artificial intelligence, machine learning, computation) and other disciplines is essential. A goal-oriented control system (GOCS) architecture is proposed to enable moving from how to perform a certain task to what a control system needs to perform so increase the levels of automation. The journey of the application of the EPSRC Fellowship will be briefly shared.
Short Biography
Dr. Wen-Hua Chen holds Professor in Autonomous Vehicles in the Department of Aeronautical and Automotive Engineering at Loughborough University, UK. Prof. Chen has a considerable experience in control, signal processing and artificial intelligence and their applications in aerospace, automotive and agriculture systems. In the last 15 years, he has been working on the development and application of unmanned aircraft system and intelligent vehicle technologies, spanning autopilots, situational awareness, decision making, verification, remote sensing for precision agriculture and environment monitoring. His unmanned vehicles related research is widely supported by the UK government and industry. He is a Chartered Engineer, and a Fellow of IEEE, the Institution of Mechanical Engineers, and the Institution of Engineering and Technology, UK. Recently Prof Chen was awarded an EPSRC Established Career Fellowship in developing control theory for next generation of control systems to enable high levels of automation such as robotics and autonomous systems.
Talk Title
Study on Human Centred Robotics for EPSRC Fellowship Application
Abstract
Expressing, learning and reusing skills as modularized ones can strengthen the generalization ability of skills and reusability. Human-robot shared control combines the advantages of both human and robot. This talk will introduce my research in the field of robot skill learning and human-robot shared control. I used control theory to model the control mechanism of motor neurons to assist us developing human-like robot controllers so that the robot can realize variable impedance control to adaptively physically-interact with the changing environment. I further proposed a multi-task impedance control and impedance learning method used on a human-like manipulator with redundant degrees of freedom to achieve compliant human-robot interaction motor control. Learning from human demonstration methods are generally used to efficiently transfer modularized skills to robots using multi-modal information such as surface electromyography signals and contact forces, enhancing the effectiveness of skill reproduction in different situations. I have also developed an enhanced neural-network shared control system for teleoperation, which uses the redundancy of joint space to avoid collisions automatically. The operator does not need to pay attention to possible collisions during manipulation.
Furthermore, this talk will also introduce my application of EPSRC Innovation Fellowship, by applying the abovementioned techniques to flexible manufacturing. Typically, reprogramming and operating robots for production purposes can pose significant challenges for businesses, which could be potential barriers to automation and corporate expansion. I proposed to address these issues by increasing flexibility of robot operation based on human robot interaction.
Short Biography
Prof. Chenguang Yang is the leader of Robot Teleoperation Group of Bristol Robotics Laboratory. He received the Ph.D. degree in control engineering from the National University of Singapore, Singapore, in 2010, and postdoctoral training in human robotics from the Imperial College London, London, U.K. He was awarded EU Marie Curie International Incoming Fellowship (individual) grant and UK EPSRC UKRI Innovation Fellowship grant. He won the Best Paper Award of the IEEE Transactions on Robotics as well as over ten international conference Best Paper Awards. He is a Fellow of British Computer Society and a Fellow of Higher Education Academy. He is a Co-Chair of IEEE Technical Committee on Collaborative Automation for Flexible Manufacturing (CAFM) and a Co-Chair of IEEE Technical Committee on Bio-mechatronics and Bio-robotics Systems (B2S). He serves as Associate Editors of a number of international top journals including Neurocomputing and seven IEEE Transactions. He is supervisor of an H2020 Marie Sklodowska-Curie Standard European Fellow. His research interest lies in human robot interaction and intelligent system design.
Talk Title
Multidomain Vibration-Absorber Synthesis: Fellowship Application and Project Progress
Abstract
In this talk, I will first share my fellowship application experience – this includes proposal drafting, presentation and interview preparation. Each aspect will be linked with the awarded EPSRC fellowship on ‘Multidomain Vibration-Absorber Design’. In the second part of this talk, I will introduce the up-to-date project progress. Traditional vibration-absorber design approaches rely on introducing specific modifications to existing designs – this leaves huge performance possibilities unexplored. The developed synthesis-based methodology enables optimum designs to be constructed considering components from the mechanical, hydraulic, pneumatic, and electrical domains. The significant performance advantages will then be demonstrated for multiple mechanical systems, for both vibration suppression and passive-active-combined motion control purposes.
Short Biography
Dr. Jason Zheng Jiang received the B.Sc. and M.Sc. degrees in electrical and electronic engineering from Shanghai Jiao Tong University. He was awarded a PhD from the University of Cambridge in 2010. Dr Jiang joined University of Bristol in 2013 as a Lecturer. He was promoted to Senior Lecturer and Associate Professor respectively in 2018 and 2021. He holds an EPSRC Research Fellowship and serves as the Academic Lead of the Vibration Suppression Research Unit, Dynamics and Control Research Group. He won as PI £2.2M research funding to date from Research Councils and Industry. Dr Jiang’s research focuses on vibration suppression, network synthesis theory, passive-active-combined motion control. He has long-standing research collaborations with industrial stakeholders from Automotive, Wind Energy, Rail, and Civil sectors.
Research Workshop 17th January 2021
Talk Title
Smart Factory at your Fingertips
Abstract
Driven by breakthroughs in emerging technologies such as Internet of Things (IoTs), cloud computing, big data, artificial intelligence (AI) and robotics, digital transformation is considered central to improved productivity for UK Industry which has long lagged behind that of its competitors. The positive impact of faster innovation and adoption of industrial digitalization technologies (IDTs) could be as much as £455 billion for UK manufacturing over the next decade (Accenture report: 2017 Industrial Digitalisation Review Benefit Analysis).
The talk presents a new concept of “smart factory at your fingertips” as a cross-sectional solution to fully exploit the benefit of IDTs for future manufacturing systems to achieve the ambitious productivity gains setup in the UK Industrial Strategy. It starts from a review of historical stages of manufacturing technology and system, and then focuses on initial application cases and technological challenges for applying IDTs to fulfil the vision of “smart factory at your fingertips” concept from a perspective of a precision manufacturing researcher. The talk concludes with several open-ended questions as potential starting points for research collaborations between computing, automation & control, and manufacturing science and technology researchers.
Short Biography
Xichun Luo is a Professor in ultra precision manufacturing and technical director of Centre for Precision Manufacturing (CPM) at the University of Strathclyde (Glasgow). He is an elected Fellow of the International Society for Nanomanufacturing, the International Academy of Engineering and Science and the International Association of Advanced Materials. He is an associate editor for Proceeding of IMechE Part C: Journal of Mechanical Engineering Science, Journal of Micromanufacturing and Journal of Nanomanufacturing and Metrology. His research has been founded by the EPSRC, EC, Royal Society and Industry. His research interests include ultra precision machining, digital manufacturing, hybrid micromachining and nanomanufacturing, as evidenced by two books and more than 120 papers in peer-reviewed highly ranked journals. He won UK Institution of Mechanical Engineers (IMechE) 2015 Ludwig Mond Prize for his work in the application of digital technology in micro- and nano-manufacturing.
Talk Title
State estimation and charging control of battery storage systems
Abstract
The global economy will be greatly shaped by the transformed energy landscapes. Energy storage systems, in particular battery storage systems play an important role in decarbonizing the whole energy chain from accepting renewable generations to electrification of transport and other sectors. The talk presents some recent studies in the modelling and charging control of battery storage systems.
Short Biography
Professor Kang Li holds the Chair of Smart Energy Systems at University of Leeds, UK. His primary research interest lies on the development of advanced modelling, control and optimization methods in the energy and manufacturing fields, contributing to the decarbonization of energy chain from top to tail, including renewable generation, electrification of transport, decarbonization of manufacturing, and novel battery technologies used in these applications. His work on the development of minimal-invasive cloud based energy and condition monitoring platform (Point Energy Technology) has been successfully used in food processing and polymer processing industries, winning InstMC ICI prize 2015, Northern Ireland INVENT 2016 award, finalist of Sustainable Energy Awards 2016 from Sustainable Energy Authority of Ireland, and Outstanding Award from Knowledge Transfer Partnerships 2015. He has published over 180 international journal papers and edited 17 international conference proceedings in his area, winning over 10 national and international prizes and awards, including the most recent Springer Nature ‘China New Development Award’ in 2019 in recognition of the ‘exceptional contributions to the delivery of the UN Sustainable Development Goals’.