Prof. Yoshihiko Nakamura
Methods, Data and Value of Human Motion Analysis
Time：09:00-10:00, Thursday, December 13, 2018 Location: Conference Hall 1
Abstract: Robotics technlogy has developed sensors, algorithms, and systems for human motion analsysis. The data of human motion is the key for human-robot systems as well as for human healthcare systems. This talk shares our development of algorithms and software for the computation of human nuero musculoskeletal model and experience of human motion analysis of athletes and experts. The recently developed video-based motion capture system opens the door to the big-data era of human motion analysis. The technology and the scope on the value of data will also be discussed.
Biography: Yoshihiko Nakamura is Professor at Department of Mechano-Informatics, University of Tokyo. He received Ph.D from Kyoto University. Humanoid robotics, cognitive robotics, neuro musculoskeletal human modeling, and their computational algorithms are his fields of research. Dr. Nakamura served as President of IFToMM (2012-2015). He is Foreign Member of Academy of Engineering Science of Serbia, TUM Distinguished Affiliated Professor of Technische Universitat Munchen, Executive Member of International Foundation of Robotics Research, and Fellow of JSME, RSJ, IEEE, and World Academy of Art and Science.
Prof. Metin Sitti
Bio-inspired Small-Scale Soft Robotics
Time：09:00-10:00, Friday, December 14, 2018 Location: Conference Hall 1
Abstract: Inspired by soft-bodied animals, soft functional active materials could enable physical intelligence for small-scale (from a few millimeters down to a few micrometers overall size) robots by providing them unique capabilities, such as shape changing and programming, physical adaptation, safe interaction with their environment and multi-functional and drastically diverse dynamics. In this talk, our recent activities on design, manufacturing, and control of new bio-inspired shape-programmable active soft matter and untethered soft robots at the milli/microscale are reported. First, elastomeric microfibers, inspired by gecko foot-hairs, are proposed as new reversible soft adhesives for robotics, as soft robotic gripper and climbing robot attachment materials, skin adhesives for soft wearable devices, etc. Second, red blood cell (RBC)-based soft microswimmers driven by attached E. coli bacteria are proposed as new active local drug delivery systems. These microswimmers carry cargo such as drugs and imaging agents inside the RBC, can be steered magnetically, and can be fully degraded via exposed NIR light. Third, untethered soft millirobots inspired by spermatozoids, caterpillars and jellyfishes are proposed using elastomeric magnetic composite materials. Static and dynamic shapes of such magnetic active soft materials are programmed using a computational design methodology. These soft robots are demonstrated to be able to have seven or more locomotion modalities (undulatory swimming, jellyfish-like swimming, water meniscus climbing, jumping, ground walking, rolling, crawling inside constrained environments, etc.) in a single robot for the first time to be able to move on complex environments, such as inside the human body. Preliminary ultrasound-guided navigation of such soft robots is presented inside an tissue towards their medical applications to deliver drugs and other cargo locally and heat the local tissues for hyperthermia and cauterization.
Biography: Metin Sitti received the BSc and MSc degrees in electrical and electronics engineering from Bogazici University, Istanbul, Turkey, in 1992 and 1994, respectively, and the PhD degree in electrical engineering from the University of Tokyo, Tokyo, Japan, in 1999. He was a research scientist at University of California at Berkeley, USA during 1999-2002 and a professor in Department of Mechanical Engineering and Robotics Institute at Carnegie Mellon University, USA during 2002-2016. Since 2014, he has been the director of the Physical Intelligence Department at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. His research interests include small-scale physical intelligence, mobile milli/microrobots, bio-inspiration, and medical robotics. He is an IEEE Fellow. He received the Rahmi Koç Science Prize in 2018, SPIE Nanoengineering Pioneer Award in 2011, and NSF CAREER Award in 2005. He received many best paper and video awards in major conferences. He is the editor-in-chief of Journal of Micro-Bio Robotics and Progress in Biomedical Engineering and associate editor in Extreme Mechanics Letters, Advanced Material Technologies, and Biomimetics & Bioinspiration journals.
Prof. Daniel D. Lee
Machine Learning in Autonomous Systems: Theory and Practice
Time：13:30-14:30, Friday, December 14, 2018 Location: Conference Hall 1
Abstract: Current artificial intelligence (AI) systems for perception and action incorporate a number of techniques: optimal observer models, Bayesian filtering, probabilistic mapping, trajectory planning, dynamic navigation and feedback control. I will briefly describe and demonstrate some of these methods for autonomous driving and for legged and flying robots. In order to model data variability due to pose, illumination, and background changes, low-dimensional manifold representations have long been used in machine learning. But how well can such manifolds be processed by neural networks?I will highlight the role of neural representations and discuss differences between synthetic and biological approaches to computation and learning.
Biography：Dr. Daniel D. Lee is currently Professor in Electrical and Computer Engineering at Cornell Tech and Executive Vice President for Samsung Research. He previously was the UPS Foundation Chair Professor in the School of Engineering and Applied Science at the University of Pennsylvania. He received his B.A. summa cum laude in Physics from Harvard University and his Ph.D. in Condensed Matter Physics from the Massachusetts Institute of Technology in 1995. After completing his studies, he was a researcher at AT&T and Lucent Bell Laboratories in the Theoretical Physics and Biological Computation departments. He is a Fellow of the IEEE and AAAI and has received the National Science Foundation CAREER award and the Lindback award for distinguished teaching. He was also a fellow of the Hebrew University Institute of Advanced Studies in Jerusalem, an affiliate of the Korea Advanced Institute of Science and Technology, and organized the US-Japan National Academy of Engineering Frontiers of Engineering symposium and Neural Information Processing Systems (NIPS) conference. His research focuses on understanding general computational principles in biological systems, and on applying that knowledge to build intelligent robotic systems that can learn from experience.
Prof. Dong-Soo Kwon
Flexible Endoscopic Surgery Robots
Time：09:00-10:00, Saturday, December 15, 2018 Location: Room 408-409
Abstract: This talk will present research on flexible surgical robotics of KAIST center for future Medical robotics. We believe that surgical robots should be developed considering the benefits to surgeons with easy and intuitive control, to patients with minimum invasiveness and fast recovery, and to hospitals with affordable cost and reduction of surgery time.
In order to meet these requirements, firstly, EasyEndo has been developed for solo-endoscopic procedures. By attaching a motor pack to a conventional endoscope, EasyEndo allows easy and intuitive endoscopy without assistants. Second, Portable Endoscopic Tool Handler (PETH) has been developed for more advanced procedures with additional surgical arms attached to the conventional endoscope. Several ex-vivo experiments have shown the improved performance of conventional endoscope and the feasibility of PETH. Third, K-FLEX has been developed that can perform dexterous robotic surgery through a flexible pathway by adding small robot arms to the flexible endoscope. An attractive feature of these robot arms is that they can exert a great deal of force to lift organs and tissues with specially designed constraint joint mechanism. Several bench-top tests and in-vivo animal experiments had shown effectiveness and feasibility of K-FLEX on endoscopic procedures. Its technical superiority and potential for clinical use were evaluated highly that K-FLEX had won Overall Winner and Best Application Award at Surgical Robot Challenge 2018. With these robot technologies, we believe that surgeons and endoscopists can conduct a challenging surgery that has not been tried before.
Biography: Dong-Soo Kwon is a Professor in the Department of Mechanical Engineering at the Korea Advanced Institute of Science and Technology (KAIST), Director of the Human-Robot Interaction Research Center, Director of the Center for Future Medical Robotics. He is serving the IEEE Robotics and Automation Society (RAS) as a member of the Administrative Committee (AdCom). In addition, He is the founder CEO of EasyEndo Surgical Inc., Chairman of the board of directors of Korea Institute of Robot and convergence (KIRO), and a member of National Academy of Engineering of Korea (NAEK).
His research deals with Medical Robotics, Haptics, and Human-Robot Interaction. He has contributed to the advancement of several robot venture companies by technology transfer. Recently, he has established a start-up company based on his medical robot research results.He had worked as the Research Staff in the Telerobotics section at Oak Ridge National Laboratory from 1991 to 1995. He was a Graduate Research Assistant in Flexible Automation Lab. at Georgia Institute of Technology from 1985 to 1991, and the Section Chief, Manager at R&D Group of Kanglim Co., Ltd from 1982 to 1985. He received the Ph.D. in the Department of M.E. at Georgia Institute of Technology in 1991, M.S. in the M.E. at KAIST in 1982, and B.S. in the M.E. at Seoul National University in Korea in 1980.
Based on our research experience over the last 20 years, we are planning to commercialize our research outputs. Our flexible robot technologies will extend endoscope application from conventional endoscopy procedure to robotic surgery.
Prof. Gursel Alici
Soft Robotics for Prosthetic Devices; Research Challenges and Opportunities
Time：13:30-14:00, Thursday, December 13, 2018 Location: Room 401-402
Abstract: As a continuously growing field of robotics, soft robotics is the science and engineering of the robots primarily made of soft materials, components and monolithic active structures such that these soft robots can safely interact with and adapt to their environment better than the robots made of hard components. Soft robotics offers unprecedented solutions for applications involving safe interaction with humans and objects, and manipulating and grasping fragile objects, crops and similar agricultural products. The progress in soft robotics will have a significant impact especially on medical applications such as wearable robots, prosthetic devices, assistive devices, and rehabilitation devices. Soft materials with programmable mechanical, electrical and rheological properties, and conformable to additive manufacturing based on 3D printing are essential to realize soft robots.
In this talk, after briefly describing what characteristics differentiate the field of soft robotics from the conventional hard robotics, we will try to answer the question of where we are in soft robotics to establish prosthetic hands with features that will bring them one-step closer to their natural counterparts. The primary feature of such a prosthetic hand is to interpret and receive the hand user’s intention noninvasively, and equally importantly send sensory feedback about the state of a prosthetic hand to its user noninvasively in order to help “restore normality” for prosthetic hand users. We will also present the progress we have made in the establishment of a fully 3D printed transradial prosthetic hand at our center of excellence, ACES, at University of Wollongong. We hope to create a medium of discussion and interaction among the conference delegates and hence contribute to the consolidation of an effectual bridge between robotics, upper-limb prosthetic devices, bionics and materials research in order to deliver the expected outcomes of soft robotics for prosthetic and rehabilitation devices in a timely manner.
Biography: Gursel Alici received the Ph.D. degree in Robotics from the Department of Engineering Science, Oxford University, Oxford, U.K., in 1994. He is currently a Senior Professor at the University of Wollongong, Wollongong, Australia, where he is the Head of the School of Mechanical, Materials. Mechatronic and Biomedical Engineering since 2011. His research interests are soft robotics, system dynamics and control, robotic drug delivery systems, novel actuation concepts for biomechatronic applications, robotic mechanisms and manipulation systems, soft and smart actuators and sensors, and medical robotics. He has published more than 300 refereed publications and delivered numerous invited seminars and keynote talks on his areas of research.
Dr. Alici was a Technical Editor of the IEEE/ASME Transactions on Mechatronics during 2008–2012. He is a Technical Editor of the IEEE Access, the first IEEE open access journal with interdisciplinary scope. He has served on the international program committee of numerous IEEE/ASME International Conferences on Robotics and Mechatronics. He was the General Chair of the 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics held in Wollongong, Australia. He is the leader of Soft Robotics for Prosthetic Devices theme of the ARC Center of Excellence for Electromaterials Science. He received the Outstanding Contributions to Teaching and Learning Award in 2010, the Vice-Chancellor’s Interdisciplinary Research Excellence Award in 2013, and Vice-Chancellor’s Award for Research Supervision in 2018 from the University of Wollongong. He has held a visiting professorship position at Swiss Federal Institute of Technology, Lausanne (EPFL), City University of Hong Kong, and University of Science and Technology of China (USTC).
Prof. Helge Ritter
From AI to Biomimetic Intelligence
Time：13:30-14:00, Thursday, December 13, 2018 Location: Room 406-407
Abstract: The convergence of recent advances in machine learning, processing power and the availability of huge datasets have enabled important breakthroughs in AI. Impressive examples include achieving super-human performance in object recognition, board games, poker, or end-to-end learning in computer games. However, in the majority of these impressive examples embodiment and physical interaction play no or only a very limited role – in stark contrast to biomimetic systems, where embodiment and physical interaction are key characteristics. Therefore, creating tighter connections between current AI and machine learning approaches and biomimetic systems – creating “biomimetic intelligence” – poses challenges that only have begun to become addressed – e.g. in some very recent deep learning approaches to solve grasping and manipulation for robot hands.We will present some of these challenges with an emphasis on tactile interaction and how bio-inspired approaches can lead to advanced tactile sensors, how the potential of these sensors can be tapped with the aid of current machine learning methods, and how this in turn helps to advance the synthesis of grasping and manipulation skills for anthropomporphic robot hands, including the connection of touch and vision, along with learning. We finally discuss how this is important to better align the interaction skills of robots with those of ourselves and along which dimensions the underlying “biomimetic intelligence” will need to become further extended for a human-compatible embedding of robots into our society at large.
Biography: Helge Ritter studied Mathematics and Physics at the Universities of Bayreuth and Heidelberg and obtained a PhD in Theoretical Physics at TU Munich in 1988. After research stays at Helsinki University of Technology and at the University of Illinois at Urbana Champaign (USA) he joined the Faculty of Technology at Bielefeld University where he is leading the Neuroinformatics Group.
Helge Ritter’s main interests are principles of neural computation and, in particular, self-organising and learning systems, and their application to robot control, manual intelligence, machine vision, data analysis and interactive human-machine interfaces. He has authored or co-authored numerous papers in these fields.In 1999 Helge Ritter was awarded the SEL Alcatel research prize and in 2001 the Leibniz Prize of the German Science Foundation. He is a member of the Scientific Advisory Council of the ZiF, the Faculty of the Parmenides Foundation, the Scientific Advisory Board of the Max Planck Institute for Intelligent Systems, the NRW Academy of Sciences, and the German Academy of Science and Engineering (acatech). He is a founding member and Director of the Institute for Cognition and Robotics (CoR-Lab) and since 2007 Coordinator of the Excellence Cluster Cognitive Interaction Technology, both at Bielefeld University.
Prof. Ruigang Yang
Baidu’s RAL: From Autonomous Driving to Robotics
Time：13:30-14:00, Saturday, December 15, 2018 Location: Room 401-402
Abstract: Baidu is the leading internet search provider in China. In the last few years, it has invested heavily in AI-related R&D. Among these projects, autonomous driving (AD) is one of the most prominent. In this talk, I will introduce Baidu’s Apollo project that provides an open source and open capability platform for autonomous driving. In addition, I will introduce the newly founded Robotics and Autonomous Driving lab (RAL) in Baidu Research, which serves as the research arm for AD business and the exploration front for robotics research.
Biography: Ruigang Yang is currently Chief Scientist for 3D Vision at Baidu Research. He leads the Robotics and Autonomous Driving Lab (RAL). Before joining Baidu. He was a full professor of Computer Science at the University of Kentucky. He obtained his PhD degree from University of North Carolina at Chapel Hill and his MS degree from Columbia University. His research interests span over computer graphics and computer vision, in particular in 3D reconstruction and 3D data analysis. He has published over 100 papers, which, according to Google Scholar, has received over 10000 citations with an h-index of 48 (as of 2017). He has received a number of awards, including US NSF Career award in 2004, best demonstration award in CVPR 2006, and University of Kentucky’s Dean’s Research Award in 2013. He is currently an associate editor of IEEE TPAMI and a senior member of IEEE.
Prof. Wataru Takano
Artificial Intelligence for Human/Robot Movements
Time：13:30-14:00, Saturday, December 15, 2018 Location: Room 406-407
Abstract: Human activities come in a variety of forms and styles. We can handle their variety during recognizing human actions, and performing our own action upon the environment. To realize these functions in robots, one key technique is to encode the activities into multiple simple forms of a mathematical model. This is referred to as symbolization. Since the simple symbol removes the realistic properties in the movements, it is impossible to generate a feasible motion for a robot only from the symbol. Another key technique is to construct a control theory based on robot kinematics and dynamics to realize the robot movements. The design of the motion symbol and the control theory built on the foundation of each other is required for robotics and artificial intelligence. This talk introduces the mathematical model for human activities and its connection to natural language that is a symbolic system unique to humans. Additionally, we present a computational algorithm to generate a robot motion that is similar to human activities and that satisfies the physical consistency.
Biography: Wataru Takano is a Specially Appointed Professor at a Center for Mathematical Modeling and Data Science, Osaka University. He received the B.S and M.S degrees from Kyoto University, Japan, in precision engineering in 1999 and 2001, Ph.D degree from Mechano-Informatics, the University of Tokyo, Japan, in 2006. He was a Lecturer, and an Associate Professor at the University of Tokyo from 2009 to 2015, and from 2015 to 2017. He was a Researcher on Project of Information Environment and Humans, Presto, Japan Science and Technology Agency from 2010 to 2014. He is the Co-Chair of IEEE-RAS Technical Committee on Robot Learning. His research interests are stochastic model, kinemaitics/dynamics computation, and control theory in data science and robotics. He has received several awards from IEEE conference on Humanoids 2005, Robotics society of Japan 2010, Japanese Society for Artificial Intelligence2014, Society of Instrument and Control Engineers, System Integration Division 2015, IEEE conference on Intelligent Robots and Systems 2018.