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Prof. Hiroshi Ishiguro
Intelligent Robotics Lab,
Osaka University, Japan.

Hiroshi Ishiguro (石黒浩 Ishiguro Hiroshi) is director of the Intelligent Robotics Laboratory, part of the Department of Systems Innovation in the Graduate School of Engineering Science at Osaka University, Japan. A notable development of the laboratory is the Actroid, a humanoid robot with lifelike appearance and visible behaviour such as facial movements. In robot development, Ishiguro concentrates on the idea of making a robot that is as similar as possible to a live human being. At the unveiling in July 2005 of the gynoid Repliee Q1Expo (in the cybernetic world, the term for female android, gynoid, from ancient Greek "gyne", that is woman) he was quoted as saying, "I have developed many robots before, but I soon realised the importance of its appearance. A human-like appearance gives a robot a strong feeling of presence. ... Repliee Q1Expo can interact with people. It can respond to people touching it. It's very satisfying, although we obviously have a long way to go yet." In his opinion, it may be possible to build an android that is indistinguishable from a human, at least during a brief encounter. Ishiguro has made an android that resembles him, called the Geminoid. The Geminoid was among the robots featured by James May in his 5 October 2008 BBC2 documentary on robots Man-Machine in May's series Big Ideas. He also introduced a telecommunication robot called the Telenoid R1. Hiroshi also uses the android to teach his classes at Osaka University of Japan and likes to scare his students by making Geminoid do human-like movements like blinking, "breathing" and fidgeting with his hands. Ishiguro has been listed, in 2011, as one of the 15 Asian Scientists to Watch by Asian Scientist Magazine. In 2018, Ishiguro was interviewed interacting with one of his robots for the documentary on artificial intelligence Do You Trust This Computer?.
Interactive Intelligent Robots and Our Future


Abstract: The speaker has been working on the research and development of autonomous robots that interact with people in the JST ERATO Ishiguro Symbiotic Human Robot Interaction Project. The research approach involved is called the constructive method. This methodology reproduces complicated social phenomena, whose underlying principles are unknown, with robots in order to investigate the underlying mechanisms. By combining the various elements necessary for the realization of intelligent robots, we will develop a robot that behaves and interacts like a human. If this robot conveys human meta-level cognitive functions, such as intelligence, emotions, and consciousness through dialogue, the mechanisms of the robot will give us hints for clarifying the mechanisms underlying the meta-level cognitive functions. In this talk, the speaker will introduce research on autonomous conversational androids which have intentions and desires and integrate various implementable technologies, tele-operated androids, and social conversational robots, as examples of the constructive method. We will then discuss the potential of this method both for scientific research and practical application.

Intelligent Robotics Laboratory, Osaka University


A Perceptual Information Infrastructure monitors and recognizes real environment through sensor networks. The sensor network tracks people in real-time and recognizes human behaviors which provide rich information for understanding real world events and helps peoples and robots working in the real world. An Intelligent Robot Infrastructure is an interaction-based infrastructure. By interacting with robots, people can establish nonverbal communications with the artificial systems. That is, the purpose of a robot is to exist as a partner and to have valuable interactions with people. Our objective is to develop technologies for the new generation information infrastructures based on Computer Vision, Robotics and Artificial Intelligence. Introduction(PDF)

Prof. Davide Scaramuzza
Professor of Robotics and Perception,
University of Zurich.

Davide Scaramuzza is a Professor of Robotics and Perception at the University of Zurich, where he does research at the intersection of robotics, computer vision, and machine learning, using standard cameras and event cameras, and aims to enable autonomous, agile navigation of micro drones in search and rescue applications. For his research contributions, he won prestigious awards, such as a European Research Council (ERC) Consolidator Grant, the IEEE Robotics and Automation Society Early Career Award, a Google Research Award, and two Qualcomm Innovation Fellowships. In 2015, he cofounded Zurich-Eye, today Facebook Zurich, which developed the visual-inertial SLAM system running in Oculus Quest VR headsets. He was also the strategic advisor of Dacuda, today Magic Leap Zurich. Many aspects of his research have been prominently featured in wider media, such as The New York Times, BBC News, Discovery Channel.
Autonomous, Agile Micro Drones:
Perception, Learning, and Control


Abstract: Autonomous quadrotors will soon play a major role in search-and-rescue, delivery, and inspection missions, where a fast response is crucial. However, their speed and maneuverability are still far from those of birds and human pilots. High speed is particularly important: since drone battery life is usually limited to 20-30 minutes, drones need to fly faster to cover longer distances. However, to do so, they need faster sensors and algorithms. Human pilots take years to learn the skills to navigate drones. What does it take to make drones navigate as good or even better than human pilots? Autonomous, agile navigation through unknown, GPS- denied environments poses several challenges for robotics research in terms of perception, planning, learning, and control. In this talk, I will show how the combination of both model- based and machine learning methods united with the power of new, low-latency sensors, such as event cameras, can allow drones to achieve unprecedented speed and robustness by relying solely on onboard computing.

Contributions


Davide Scaramuzza is most known for:

(1) pioneering contributions to learning agile vision-based flight. video, paper, research.
(2) pioneering contributions to event-camera-based algorithms for mobile robots. 2014, 2017. Link to the research page.
(3) pioneering contributions to visual-inertial-SLAM-based autonomous navigation of micro drones. ICRA'10 paper.
(4) inventing the 1-point RANSAC algorithm, an effective and computationally efficient (1000 times faster) reduction of the standard 5-point RANSAC for visual odometry, when the vehicle motion is non-holonomic. IJCV'11 paper.
(5) authoring the Omnidirectional Camera Calibration Toolbox for MATLAB (OCamCalib), used at many companies (e.g., NASA, Philips, Bosch, Daimler, etc.). LINK. The toolbox is also part of the Matlab Computer Vision Toolbox.

Prof. Clément Gosselin
ULAVAL · Department of Mechanical Engineering,
Laval University.

Clément Gosselin received the B. Eng. degree in Mechanical Engineering from the Université de Sherbrooke in 1985, and the Ph.D. degree from McGill University in 1988. He was then a post- doctoral fellow at INRIA in Sophia-Antipolis, France in 1988-89. In 1989 he joined the Department of Mechanical Engineering at Université Laval, Québec where he is a Full Professor since 1997. He is currently holding a Canada Research Chair in Robotics and Mechatronics since January 2001. He was a visiting researcher at the RWTH in Aachen, Germany in 1995, at the University of Victoria, Canada in 1996 and at the IRCCyN in Nantes, France in 1999. His research interests are kinematics, dynamics and control of robotic mechanical systems with a particular emphasis on the mechanics of grasping, the kinematics and dynamics of parallel manipulators and the development of human-friendly robots. His work in the aforementioned areas has been the subject of numerous publications in international journals and conferences as well as of several patents and two books. He has been directing many research initiatives, including collaborations with several high-technology companies and he has trained more than 120 graduate students. He is a Senior Editor of the IEEE Robotics and Automation Letters and an associate editor of the ASME Journal of Mechanisms and Robotics. Dr. Gosselin received several awards including the ASME DED Mechanisms and Robotics Committee Award in 2008 and the ASME Machine Design Award in 2013. He was appointed Officer of the Order of Canada in 2010 for contributions to research in parallel mechanisms and underactuated systems. He is a fellow of the ASME, of the IEEE and of the Royal Society of Canada.
Parallel robots to the rescue: designing low-impedance robots for intuitive physical
human-robot interaction


Abstract: Over the past decades, parallel mechanisms have found applications in many areas including motion simulation, high-speed robots, machine-tools and cable-driven systems, to name a few. More recently, parallel and hybrid robots have been proposed in the emerging field of physical human-robot interaction (pHRI) which aims at taking advantage of the complementary capabilities of robots and humans. One of the key challenges in pHRI is to provide an intuitive physical interaction to the human user. Due to their low moving inertia, parallel robots can be used advantageously to design low-impedance mechanical interfaces in order to increase the mechanical bandwidth of the human-robot interaction, thereby leading to a very intuitive behaviour. In this presentation, the use of parallel and hybrid robots in the design of pHRI devices is proposed and examples of prototypes developed at Laval University are shown. Solutions based on passive or actuated mechanisms are illustrated. The results clearly demonstrate the capability of parallel mechanisms to provide high interaction bandwidth for pHRI robots.

Prof. Steven M. LaValle
Professor of Robotics and Virtual Reality,
University of Oulu.

Steven M. LaValle is Professor of Computer Science and Engineering, in Particular Robotics and Virtual Reality, at the University of Oulu, Finland. From 2001 to 2018, he was a professor in the Department of Computer Science at the University of Illinois. He has also held positions at Stanford University and Iowa State University. His research interests include robotics, virtual reality, sensor fusion, planning algorithms, computational geometry, and control theory. In research, he is mostly known for his introduction of the Rapidly exploring Random Tree (RRT) algorithm, which is widely used in robotics and other engineering fields. He also authored the books Planning Algorithms, Sensing and Filtering, and Virtual Reality. With regard to industry, he was an early founder and chief scientist of Oculus VR, acquired by Facebook for $3 billion in 2014, where he developed patented tracking technology for consumer virtual reality and led a team of perceptual psychologists to provide principled approaches to virtual reality system calibration, health and safety, and the design of comfortable user experiences. From 2016 to 2017, he was a Vice President and Chief Scientist of VR/AR/MR at Huawei Technologies, where he was a leader in consumer product development on a global scale.
Billiard-Like Robots:
Let Them Be Unstable and Unobservable!


Abstract: This talk will highlight our work over the past decade on controlling robots by giving them simple rules to reflect off of obstacles in their environment. This line of work pushes the extreme limits of minimalism and is suitable for scenarios where there are limited sensing and actuation capabilities, such as consumer security robots and nanorobotics. We take heavy inspiration from dynamical billiards, a branch of mathematics pioneered by Hadamard, Artin, Sinai, and others, but adapt the bouncing laws to models that are easily achievable by robots and are amenable to algorithmic analysis. Our results include basic conditions for attractors and limit cycles, simple achievement of linear-temporal logic specifications, visibility-based algorithmic analysis, and demonstrations on embarrassingly cheap robot systems. An abundance of simple, open problems remain in this area.

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