{"id":1290,"date":"2015-11-26T15:41:54","date_gmt":"2015-11-26T15:41:54","guid":{"rendered":"http:\/\/eodyne.hl327.dinaserver.com\/en\/?page_id=1290"},"modified":"2019-06-29T07:15:25","modified_gmt":"2019-06-29T06:15:25","slug":"plenarytalks","status":"publish","type":"page","link":"https:\/\/livingmachinesconference.eu\/2019\/plenarytalks\/","title":{"rendered":"PLENARY TALKS"},"content":{"rendered":"

Studies on Interactive Robots<\/h3>\n
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Ishiguro has contributed to establishing a new research field called Interaction in robotics. He has studied human-robot interaction and developed interactive humanoid robots designed for ordinary use. Furthermore, he has developed the world<\/span>\u2019<\/span>s first realistic humanoid robot called android.\u00a0<\/span>In this talk, he will introduce various interactive personal robots and androids and explain how to study the technologies and scientific issues by using them.\u00a0<\/span>Especially, he will focus on embodiment, emotion and intention\/desire of the robots and androids. And further, he will discuss on our future society where we have symbiotic relationships with them<\/span><\/p>\n<\/div>\n<\/div><\/div><\/div>

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\"\"<\/a>Hiroshi\u00a0Ishiguro<\/a><\/strong>\u00a0received a D. Eng. in systems engineering from the Osaka University, Japan in 1991. He is currently Professor of Department of Systems Innovation in the Graduate School of Engineering Science at Osaka University (2009-) and Distinguished Professor of Osaka University (2017-). He is also visiting Director (2014-) of Hiroshi Ishiguro Laboratories at the Advanced Telecommunications Research Institute and an ATR fellow. His research interests include sensor networks, interactive robotics, and android science.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

Navigation, Neuroscience and Neural Networks: A Quest to Understand Intelligence and Build Better Technology for Robots and Autonomous Vehicles<\/h3>\n
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The goal of my research is to understand the fundamental nature of intelligence, so that we can both shed light on how the brain functions, and create intelligent, autonomous systems that transform society. We draw inspiration from the amazing natural world including animal species like rats, insects, primates, and humans, combined with robots, algorithms, innovative sensing modalities, computational neuroscience and artificial neural networks of all types. I\u2019ll summarize a roboticist\u2019s perspective on the neuroscience underlying one of the most well understood aspects of intelligence \u2013 spatial intelligence and perception \u2013 and describe how we have adapted this knowledge to create landmark robotics advances including RatSLAM\u2019s mapping of an entire suburb using only webcam, persistent long term robot navigation autonomy trials and robust anytime localization. Finally, I\u2019ll highlight how we are translating fundamental transdisciplinary science into industrial applications, working with major multinational companies in domains including autonomous vehicles and automated hazard detection.<\/p>\n<\/div>\n<\/div><\/div><\/div>

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Michael Milford<\/a><\/strong> conducts interdisciplinary research at the boundary between robotics, neuroscience, machine learning, and computer vision and is a multi-award winning educational entrepreneur. His research models the neural mechanisms in the brain underlying tasks like navigation and perception in order to develop new robotics and computer vision-related technologies, with a particular emphasis on challenging application domains where current techniques fail such as all-weather, anytime positioning for autonomous vehicles. He is also one of Australia\u2019s most in-demand experts in technologies including self-driving cars, robotics, and artificial intelligence, and is a passionate science communicator. He currently holds the position of Full Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator at the Australian Centre for Robotic Vision.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

Neuromorphic Engineering: the nervous system for living machines?<\/h3>\n
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In this talk,\u00a0I will discuss Neuromorphic Engineering, it\u2019s history, and why it is such a hot topic today. Neuromorphic Engineering is a branch of Electrical Engineering, that takes its inspiration from the neural systems in biology to develop efficient signal processing systems, particularly for perceptual tasks. Since Neuromorphic Engineering has its roots in modelling biological senses and the nervous system, it is only natural to ask if it is the logical choice for implementing the nervous system of living machines. My talk will discuss this topic.<\/p>\n<\/div>\n<\/div><\/div><\/div>

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Andre van Schaik<\/strong><\/a>\u00a0received the M.Sc. degree in electrical engineering from the University of Twente, Enschede, The Netherlands, in 1990 and the Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1998.\u00a0\u00a0In 2011 Andr\u00e9 became a research professor at Western Sydney University and presently he is\u00a0Director of the International Centre for Neuromorphic Engineering<\/a>. His research focuses on three main areas: neuromorphic engineering, bioelectronics, and neuroscience. He was identified as a world leader in neuromorphic engineering research in May 2006 by an independent article in IEEE Spectrum, the IEEE largest circulation magazine. He has authored more than 200 papers and is an inventor of more than 35 patents and he is a founder of three start-up companies: VAST Audio, Personal Audio, and Heard Systems.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

Soft Body as Source of Intelligence<\/h3>\n
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We have been working on hard robots consisting of rigid links, electric motors or hydraulic actuators for a long time. We have succeeded in a lot of tasks by utilizing precise control. However, looking at humans, our body is consisting of soft material and the control is very imprecise. Nevertheless, humans can behave adaptively and can realize amazing task performance. One of the underlying mysteries there is soft morphology of our body. Our body is well-designed though long-time evolution, and its morphology plays a great role to realize adaptive behavior. Especially, the soft muscular-skeletal structure is supposed to be very important. I will talk about our endeavors to understand the role of our soft body by building muscular-skeletal humanoid robots. I will introduce our humanoid robots, and a series of trials to generate a hypothesis on our soft body. Such a hypothesis will help us to build far more adaptive humanoid robots in the next generation.<\/p>\n<\/div>\n<\/div><\/div><\/div>

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\"\"<\/a>Koh Hosoda<\/a><\/strong> is a Professor at the Graduate School of Engineering Science at Osaka University. He received his PhD in mechanical engineering from Kyoto University in 1993. From 1993 to 1997, he was an Assistant Professor of Mechanical Engineering for Computer-Controlled Machinery at Osaka University. From 1997 to 2010 he was an Associate Professor at the Department of Adaptive Machine Systems, Osaka University. From 2010 to 2014, he has been a Professor at the Graduate School of Information Science and Technology, Osaka University.<\/p>\n

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Cognitive Development in Robots: A unified theory based on predictive coding<\/h3>\n
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My talk presents a neuro-inspired architecture for cognitive development. A theoretical framework called predictive coding suggests that the human brain works as a predictive machine, that is, it tries to minimize prediction error by updating the internal model and\/or acting on the environment. Inspired by this theory, I have been proposing neural network models for robots to acquire various cognitive functions as infants do. For example, the abilities to generate goal-directed actions, estimating others' goal, and helping others achieve goals have been acquired through a common process of minimizing prediction error. Individual diversity observed in developmental disorders, as well as continuity of development, has been demonstrated by modifying model parameters. The theory of predictive coding thus provides a unified framework for designing and understanding the mechanism for cognitive development.<\/p>\n<\/div>\n<\/div>\n<\/div><\/div><\/div>

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Yukie Nagai\u00a0<\/strong><\/a>received her Ph.D. in Engineering from Osaka University in 2004. She was a Post-Doctoral Researcher with the National Institute of Information and Communications Technology (NICT) from 2004 to 2006, and Bielefeld University from 2006 to 2009. She then became a Specially Appointed Associate Professor with Osaka University in 2009 and a Senior Researcher with NICT in 2017. Since April 2019, she is a Project Professor with the University of Tokyo. Dr. Nagai has been investigating underlying neural mechanisms for social cognitive development by means of computational approach. She designs neural network models for robots to learn to acquire cognitive functions based on the theory of predictive learning. She also developed head-mounted displays that simulate atypical visual perception in autism spectrum disorder (ASD), which greatly impacts on the society because they enable people with\/without ASD to better understand potential causes for social difficulties.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"

Ishiguro has contributed to establishing a new research field called Interaction in robotics. He has studied human-robot interaction and developed interactive humanoid robots designed for ordinary use. Furthermore, he has developed the world\u2019s first realistic humanoid robot called android.\u00a0In this talk, he will introduce various interactive personal robots and androids and explain how to study…<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"_links":{"self":[{"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/pages\/1290"}],"collection":[{"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/comments?post=1290"}],"version-history":[{"count":504,"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/pages\/1290\/revisions"}],"predecessor-version":[{"id":5302,"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/pages\/1290\/revisions\/5302"}],"wp:attachment":[{"href":"https:\/\/livingmachinesconference.eu\/2019\/wp-json\/wp\/v2\/media?parent=1290"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}