[Abstract] Biological morphogenesis can be seen as a self-organizing process where
a large number of cells communicate and interact locally with each other
and with the environment to form a complex shape as an emerging global
behavior under the control of a gene regulatory network. This self-organization
process is decentralized, robust to mild changes in the environment and
capable of self-healing.
This talk gives an overview of morphogenetic robotics, an emerging
subfield of developmental robotics that is concerned with the physical
development of intelligent robotic systems, including the body plan and neural
controller, using genetic and cellular mechanisms inspired from biological
morphogenesis. Morphogenetic robotics includes three main topics, namely,
morphogenetic swarm robotic systems, morphogenetic modular robots and
brain-body co-development of intelligent robots. Morphogenetic swarm robotics
deals with the decentralized self-organization of multi-robot systems using
genetic and cellular mechanisms, where a metaphor between cells and robots play
a central role. By morphogenetic modular robots, we mean the study of
morphogenetic principles for autonomous self-reconfiguration of modular robots,
where a module is mapped onto a number of cells. In both morphogenetic swarm
and modular robots, self-adaptation to environmental changes is a paramount
importance. Note however that these two systems are not absolutely separated.
It can happen that a swarm robotic system consists of modular robots which are
composed of a number of robots. Nevertheless, autonomous behavioral changes can
undergo under the governance of a unified gene regulation system. Finally,
brain-body co-development of robots, often based on an evolutionary approach,
is also a major research topic of morphogenetic robotics. Evolutionary
developmental approaches to brain-body co-design can offer us the possibility
to not only study the coupling between brain and body function, but also the
developmental bias on brain-body co-evolution.
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[Biography] Yaochu Jin received the B.Sc., M.Sc., and Ph.D. degrees, all in automatic
control from Zhejiang University, Hangzhou, China, in 1988, 1991, and 1996,
respectively, and the Dr.-Ing. Degree from Ruhr University Bochum, Germany,
in 2001.
Dr. Jin is a Professor and Chair in Computational Intelligence,
Department of Computing, University of Surrey, UK, from June 1, 2010. Priori to joining Surrey, he was
with the Honda Research Institute Europe and Honda R&D Europe, Germany from
1999 to 2010. His research interests include computational approaches to understanding
evolution, learning and development in biology, and biological approaches to complex
systems design. He has (co)edited three books and three conference proceedings,
authored a monograph, and (co)authored over 100 peer-reviewed journal and conference papers.
Dr. Jin is an Associate Editor of BioSystems,
the IEEE Transactions on Neural Networks, the IEEE Transactions on Control Systems Technology,
the IEEE Transactions on Systems, Man, and Cybernetics, Part C:
Applications and Reviews, and the IEEE Computational Intelligence Magazine.
He is a Program Chair or Co-Chair of a number of
international conferences or symposia. Dr. Jin is an invited Keynote / Plenary
Speaker on several international conferences and symposia. He is a Senior
Member of IEEE. |