| Photo Gallery | Original Image Download | |
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| 0.Registration | view | 0.Registration.zip |
| 1.Special&Plenary Sessions | view | 1.Special&Plenary Sessions.zip |
| 2.Keynote Sessions | view | 2.Keynote Sessions.zip |
| 3.Award Candidates Session | view | 3.Award Candidates Session.zip |
| 4.ISR(JIST) Journal Session | view | 4.ISR(JIST) Journal Session.zip |
| 5.Oral Sessions | view | 5.Oral Sessions.zip |
| 6.Poster Sessions | view 1 view 2 | 6.Poster Sessions.zip |
| 7.Lunches | view | 7.Lunches.zip |
| 8.Banquet | view | 8.Banquet.zip |
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Korea Robotics Society (KROS) Privacy Policy Business Registration Certificate : 214-82-07990 / President : Nak Young Chong Address : #506, The Korea Science and Technology Center, (635-4,Yeoksam-dong) 22, 7Gil, Teheran-ro, Gangnam-gu, Seoul, Korea SECRETARIATTEL +82-2-783-0306, FAX +82-2-783-0307, E-MAIL ur@kros.org Copyright © "Ubiquitous Robots 2023. |
| Elliott J Rouse University of Michigan Auctions, preferences, and wearable robots: the development of meaningful exoskeletons and robotic prostheses |
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Abstract Lower-limb wearable robots—such as exoskeletons and robotic prostheses—have struggled to have the societal impact expected from these exciting technologies. In part, these challenges stem from fundamental gaps in our understanding of how and why these systems should assist their wearer during use. Wearable robots are typically designed to meet a single, specific objective (e.g. reduction of metabolic rate); however, in reality, assistive technologies impact many aspects of gait and user experience. In this talk, I will discuss our recent work leveraging user preference as a ‘meta-criterion’ in design and control, through which the wearer is able to internally balance the quantitative and qualitative tradeoffs that accompany the use of wearable robots, including stability, comfort, exertion, or speed. I will highlight our work understanding user-preferred assistance settings in a variable-stiffness prosthesis and bilateral ankle exoskeletons, demonstrating user-preferred assistance settings are reliable yet diverse, and can be obtained in less than two minutes. In addition, I will discuss how user-preferred assistance can be optimized automatically with human-in-the-loop methods, which are able to converge on user-preferred settings with an accuracy of ~90%. Finally, I will introduce a new approach for understanding the success of assistive technologies using tools from behavioral economics. I will describe and quantify the economic value provided by ankle exoskeletons, including the cost incurred from wearing the added mass, as well as the value added by the assistance alone. Together, this talk will underscore the role of the user in the development of wearable robots, and advocate for a shift away from the conventional, single-objective assessment of these technologies. Biography |
| Jinoh Lee DLR Extension of Operational Space Control Enhancing Fault-Tolerance in Actuation Failure |
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Abstract Actuation failure and fault-tolerant control have drawn more attention in accordance with the recent increasing demand for reliable robot control applications for long-term and remote operations. The emergence of control torque loss, i.e., the free-swinging failure, is particularly challenging when the robot performs dynamic operational space tasks due to complexities stemming from redundancies in the kinematic structure as well as a dynamical disturbance in the under-actuated multi-body system. In this task, a dynamic analysis and control method will be introduced in line with the operational space formulation approach to address such a problem of under-actuated systems without constrained conditions, which has been overlooked yet encompasses a broader range of applications involving free-floating robots and manipulators with passive joints. Biography |
| Chung Hyuk Park George Washington University HRI and AI for Assistive and Healthcare Robotics |
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Abstract Assistive robotics is an expanding field of research that holds potential for impacting human health and enhancing quality of life. In this presentation, I will discuss my research activities focused on three main themes. Firstly, I will explore the concept of social robots as embodied agents with multi-modal intelligent perception. Secondly, I will delve into the realm of robotic learning, specifically targeting interactive learning and socio-emotional and physical interactions for autistic individuals. Lastly, I will examine contextual and mutual learning for personalized interaction, with the ultimate goal of facilitating long-term human-robot interaction. Along with my research endeavors, I will also impart the experiences and knowledge gained from cross-disciplinary studies and translational research, aimed at advancing assistive robotics for healthcare and personalized interventions. Biography |
| Dongkyu Choi A*STAR Cognitive Architecture for Collaborative Robots |
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Abstract Cognitive architectures provide infrastructure for modelling general intelligence. They make commitments to specific representation of knowledge, organization of memory, and processes that work over these structures. When integrated with facilities for embodiment including sensory perception and physical manipulation, such architectures can serve as an excellent framework for robotic agents. We take this approach to develop a robotic software based on a cognitive architecture, ICARUS, that enables natural collaboration between humans and robots by integrating multi-modal perception, dialogue capabilities, data-driven action model learning, and common-sense reasoning. In this talk, we will present an overview of this software framework and show some motivating examples of its use in realistic scenarios. We will also discuss directions for further study in this context to facilitate future adaptation of this framework in industrial applications. Biography |
| Marco Hutter ETH Zurich Towards Ubiquitous Legged Robots |
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Abstract In the last years, legged and in particular quadrupedal robots have become ubiquitous – both for academia and industry. Not only robotics researchers, but also experts in computer vision and machine learning adopt quadrupedal robots as demonstrators to study and deploy new methods to make these systems more agile and autonomous. In this presentation, I will provide insights into some of our newest research in control, perception and autonomy of quadrupedal robots. I will show how reinforcement learning has revolutionized locomotion performance, and present new ways of including perception to enable versatile navigation. Moreover, we will look at different application examples from academia and industry to provide inspiration for the future or mobile robotics.
Biography |
| Yunkyung Kim Amazon I See You: Humans with Robots in the Field |
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Abstract As robots are being used in various industries with its benefit such as increasing the speed of production, reducing human error, avoiding accidents, etc., user groups who will face with robots are also diverse. Some robots are only used by the selected and highly trained small group of people while some other robots are used by wide range of people. In this talk, different approach on validating user experience with robots depending on characteristics of user groups will be introduced. Biography |
| Tadayoshi Aoyama Nagoya University Macro-Micro Interaction Systems for Assisted Reproductive Technology |
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Abstract Human augmentation is a technology that extends human capabilities through technology. The concept of human augmentation began with microscopes and telescopes that augmented human vision. So far, humans have extended their own capabilities and activity space through technology. In this talk, I will introduce our work on macro-micro interaction technology, which extends the human activity space into micro-space; then, I will describe its prospects as a support system that simplifies Assisted Reproductive Technology. Biography He served as the secretary of Senior Program Committee (SPC) in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2022), the finance chair and secretary of 2021 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO2021), the Associated Editor (AE) of IEEE International Conference on Robotics and Automation (ICRA) since 2020, the AE of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) since 2021, and other robotics conferences. |
| Junku Yuh Korea Institute of Robotics and Technology Convergence (KIRO) ROBOTICS: Changing the Business Landscape |
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Abstract According to the World Robotics report (2022), robot installations hit a new record level in 2021 (31% increase from 2020 to 517,000 units). There are about 2.7 million industrial robots in use across the globe and roughly 400,000 new robots enter the market every year. More robots can be found in our daily lives, from cleaning robots at home, delivery robots in stores and restaurants to surgical robots in hospitals. Digital transformation, global technology competition, and social changes, due to demographic shift associated with an aging population and social distancing during the COVID-19 pandemic, have been driving the growing demand for robotics across industries and in all business sectors. This presentation consists of two parts. The first part will cover the timeline of innovation in the field of robotics highlighting technological milestones. It will also note critical areas for further development, which could help significantly expand the range of robotic applications. The second part will summarize the speaker’s research achievements during his time in Hawaii as well as current R&D activities at Korea Institute of Robotics and Technology Convergence (KIRO). Biography Dr. Yuh is an Elected IEEE Fellow and has received various prestigious awards including NSF Presidential Young Investigator Award from former President George Bush. He served as the Founding Editor-in-Chief (EIC) of Journal of Intelligent Service Robotics, Editorial Board Member of Journal of Intelligent Automation and Softcomputing, Associate Editor of IEEE Transaction on Robotics and Automation, Program Co-Chair of the IEEE 2001 and 2006 International Conference on Robotics and Automation (ICRA), and Program Chair of the IEEE 2003 International Conference on Intelligent Robots and Systems (IROS). He currently serves as a member of IEEE Fellow (Judge) Committee, IEEE Distinguished Lecturer, Advisory Board Member of Journal of Autonomous Robots, and VP of Korea Robotics Society. He has published 12 books and over 120 papers in Robotics, including Introduction to Autonomous Manipulation (G. Marani and J. Yuh) by Springer, 2014. |
| Luca Carlone MIT Spatial Perception for Robots and Autonomous Vehicles: Real-time Scene Understanding, Certifiable Robustness, and Self-training |
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Abstract Spatial perception —the robot’s ability to sense and understand the surrounding environment— is a key enabler for autonomous systems operating in complex environments, including self-driving cars and unmanned aerial vehicles. Recent advances in perception algorithms and systems have enabled robots to detect objects and create large-scale maps of an unknown environment, which are crucial capabilities for navigation, manipulation, and human-robot interaction. Despite these advances, researchers and practitioners are well-aware of the brittleness of existing perception systems, and a large gap still separates robot and human perception. This talk presents our latest results on the design of the next generation of robot perception systems and algorithms. The first part of the talk discusses spatial perception systems and motivates the need for high-level 3D scene understanding for robotics. I introduce early work on metric-semantic mapping (Kimera) and novel hierarchical representations for 3D scene understanding (3D Scene Graphs). Then, I present recent results on the development of Hydra, the first real-time spatial perception system that builds 3D scene graphs of the environment in real-time and without human supervision. The second part of the talk focuses on perception algorithms and draws connections between robustness of robot perception and global optimization. I present an overview of our certifiable perception algorithms, a novel class of algorithms that is robust to extreme amounts of noise and outliers and affords performance guarantees. I showcase applications to object pose and shape estimation and SLAM, and discuss recent results that combine learning and optimization to enable self-supervised object pose estimation. Biography |
| Tetsuya Ogata Waseda University Applications of Deep Predictive Learning for Real-World Robots |
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Abstract “Moravec’s Paradox” is one of the greatest remaining challenges in current artificial intelligence technology. For example, it is extremely difficult for robots to perform various tasks using a common hand, even with today’s state-of-the-art technology. Our proposed model of “deep predictive learning” implements the concept of “predictive coding” in neuroscience on robots. In this talk, I will introduce the results of our robotics research using this deep predictive learning and examples of joint research with multiple companies. Also I will present an overview of our Moonshot project of smart robot “AIREC” supported by Japan Cabinet Office. Biography |
