Keynote Speeches

The talk intends to highlight challenges for human machine systems. Two case studies will be presented to address the identified challenges in the speakers team in Portsmouth, UK. It requires multi-disciplinary efforts to produce an artificial hand with manipulation capabilities of the human hand. The talk will present a unified computational framework aimed at instilling human hand manipulation skills into an artificial prosthesis, with a focus on sensing, gesture recognition and skill transfer. The talk will also report recent development on gaze estimation driven solution for interacting children with autism spectrum disorders. Examples will be presented of the most recent developments in the Intelligent Systems and Biomedical Robotics Group in the field of prosthetic sensing, behaviour analytics and skill transfer.

Honghai Liu received his Ph.D degree in robotics from King¡¦s college London, UK. He is currently a Professor of intelligent systems and leads Intelligent Systems and Biomedical Robotics Group in the School of Creative Technologies at the University of Portsmouth, UK. He previously held research appointments at the Universities of London and Aberdeen, and project leader appointments in large-scale industrial control and system integration industry. He is interested in biomechatronics, pattern recognition, intelligent video analytics, intelligent robotics and their practical applications with an emphasis on approaches that could make contribution to the intelligent connection of perception to action using contextual information. He has authored/co-authored more than 200 per-reviewed journals and conference papers.

Recently, various types of intelligent robots have been developed for the society of the next generation. In particular, intelligent robots should continue to perform tasks in real environments such as houses, commercial facilities and public facilities. The growing need to automate daily tasks combined with new robot technologies are driving the development of human-friendly robots, i.e., safe and dependable machines, operating in the close vicinity to humans or directly interacting with persons in a wide range of domains. The current state of technology uses classical industrial robots, which are safely kept away from humans in cages. However, in order for robots to be used in close collaboration with humans, there are major technological challenges that need to be overcome. A robot should have human-like intelligence and cognitive capabilities to co-exist with people. The concepts on adaptation, learning, and cognitive development have to be introduced in the next generation of robots. Computational intelligence techniques, such as fuzzy, neural, and evolutionary computation can help in realizing these concepts. The most important common feature of computational intelligence techniques is that they aim at acceptably suboptimal, usually approximate solutions, while keeping the computational complexity at a tractable, usually low degree polynomial level. This is an important point when we want to realize the cognitive development of robots with low cost, in terms of both a financial and an algorithmic sense. In this talk we will briefly introduce the computational intelligence techniques and we will overview some cognitive architectures. We will emphasize the role of computational intelligence in cognitive robotics. We introduce our robot partner called iPhonoid and explain the modules and algorithms realizing its cognitive architecture. Robots can be viewed as human-centric systems since they can improve the quality of life in many areas such as supporting human activities, communication and interactions in healthcare, and welfare. However, there is a need to shift from human-centric systems to community-centric systems and improve the quality of community in social networks and communities. The role of cognitive robotics in community-centric systems will also be revealed in the talk.

Janos Botzheim¡¦s degrees earned: Budapest University of Technology and Economics: M.Sc. in Technical Informatics (2001), Ph.D. in Computer Science (2008). Visiting positions: long-term and short-term visits and scholarships as Ph.D. student at the following Universities: Czech Technical University, Prague, Czech Republic (2002, 1 month); Johannes Kepler University, Linz, Austria (4 months in 2003, 2 months in 2004, 4 months in 2005); Cracow University of Technology, Cracow, Poland (2003, 1 month); The Australian National University, Department of Computer Science, Canberra, Australia (8 months, 2005-2006). He joined the Department of Automation at the Szechenyi Istvan University, Gyor, Hungary in 2007 as a senior lecturer, in 2008 as an assistant professor, and in 2009 as an associate professor. He was a visiting researcher in the Graduate School of System Design at the Tokyo Metropolitan University from September 2010 to March 2011 and from September 2011 to February 2012. He has been an associate professor in the Graduate School of System Design at the Tokyo Metropolitan University since April 2012. Research interests: computational intelligence, automatic identification of fuzzy rule based models and some neural networks models, bacterial evolutionary algorithm, memetic algorithms, applications of computational intelligence in robotics, cognitive robotics. Membership in scientific societies: John von Neumann Computer Society, Hungarian Fuzzy Association, IEEE, IEEE Computational Intelligence Society, IEEE Robotics and Automation Society, IEEE Systems, Man, and Cybernetics Society. He has about 130 papers in journals and conference proceedings. The number of his known independent citations is about 270. He has been an invited reviewer of several scientific journals and conferences.