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Humanoid robot teleoperation system using a fast vision-based pose estimation and refinement method

IEIE Transactions on Smart Processing and Computing 2021年第1期10卷 24-30页

作者： Sa, Jae-Min Choi, Kang-Sun Interdisciplinary Program on Creative Engineering KOREATECH Cheonan-si31253 Korea Republic of Department of Electrical Electronics and Communication Engineering KOREATECH Cheonan-si31253 Korea Republic of

Humanoid robot teleoperation is a complex task that requires sophisticated hardware and software interfaces. Three-dimensional human pose estimation can be effectively applied to the teleoperation of humanoid robots thanks to its intuitive and easy usability. However, when the human pose is wrongly inferred, it can cause critical and dangerous situations for robot operation. In this paper, a reliable humanoid robot teleoperation system is proposed, which involves the operation of a humanoid robot in an isolated location. The status of the humanoid robot is monitored and communicated to the operator in real time. This improves the telepresence of scenes compared to other methods. On the operator's side, data are retrieved from the humanoid robots and manipulated to control the robot by estimating the operator's pose visually. To reduce the risk of inaccurate pose estimation, pose candidates obtained from different points of view are fused while removing irrelevant poses. Then, a simple yet effective cascade filter that generates smooth motion changes is used for stable and flexible robot manipulation. Experiments confirmed that the proposed system can functions efficiently in real time and generates more accurate motion compared to conventional systems. © 2021 The Institute of Electronics and Information Engineers

关键词： Anthropomorphic robots

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Human Pose Refinement for Reliable Robotic Teleoperation

Human Pose Refinement for Reliable Robotic Teleoperation

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Jae-Min Sa Byung-Hyun Yun Kang-Sun Choi Interdisciplinary Program on Creative Engineering KOREATECH Cheonan Korea

ISBN: (数字)9781728151861

ISBN: (纸本)9781728151878

Three-dimensional human pose estimation can be effectively applied to teleoperation of humanoids, thanks to its intuitive and easy usability. However, the human pose wrongly inferred can cause critical and dangerous situations for robotic operation. In this paper, a reliable human pose estimation method is presented. Initially, 3-D joint positions are inferred by a conventional pose estimation method using stereo images. The joint positions are refined by Kalman filtering followed by median filtering. The motor control value for each joint is smoothed with an IIR filter to perform stable and flexible operations.

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Reliable Normal Estimation from Sparse LiDAR Point Clouds

Reliable Normal Estimation from Sparse LiDAR Point Clouds

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Jae-Min Sa Seong-Jun Bae Ye-Chan Choi Kang-Sun Choi Interdisciplinary Program on Creative Engineering KOREATECH Cheonan Korea Electronics and Telecommunications Research Institute Daejeon Korea

ISBN: (数字)9781728151861

ISBN: (纸本)9781728151878

In this paper, we present a reliable vertex normal estimation method from sparse point clouds that improves the accuracy of plane-based frame-to-frame registration. We define a face normal reliability measure. The vertex normals are calculated by weighted averaging adjacent face normals based on the reliability. Through the experiments, it is confirmed that the proposed method produces consistent and reliable vertex normals.

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Federated Reinforcement Learning for Controlling Multiple Rotary Inverted Pendulums in Edge Computing Environments 2

Federated Reinforcement Learning for Controlling Multiple Ro...

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2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

作者： Lim, Hyun-Kyo Kim, Ju-Bong Kim, Chan-Myung Hwang, Gyu-Young Choi, Ho-Bin Han, Youn-Hee Korea University of Technology and Education Dept. of Interdisciplinary Program in Creative Engineering Cheon-an Korea Republic of Advanced Technology Research Center Korea University of Technology and Education Cheon-an Korea Republic of Korea University of Technology and Education Dept. of Computer Science Engineering Cheon-an Korea Republic of

ISBN: (纸本)9781728149851

Reinforcement learning has recently been studied in various fields and also used to optimally control real devices (e.g., robotic arms). In this paper, we try to allow multiple reinforcement learning agents to learn optimal control policy on their own devices of the same type but with slightly different dynamics. For such multiple devices, there is no guarantee that an agent who interacts only with one device and learns the optimal control policy will also control another device well. Therefore, we may need to apply independent reinforcement learning to each device individually, which requires time-consuming effort. To solve this problem, we propose a new federated reinforcement learning architecture where each agent working on its independent device shares their learning experience with each other, and transfers a mature policy model parameters into other agents. We incorporate the Actor-Critic PPO algorithm into each agent in the proposed collaborative architecture, and propose an efficient procedure for the gradient sharing and the model transfer. We also use edge computing to solve network problems that occur when training multiple real devices at the same time. Using multiple rotary inverted pendulum devices, we demonstrate that the proposed federated reinforcement learning scheme can effectively facilitate the learning process for multiple devices, and that the learning speed can be faster if more agents are involved. © 2020 IEEE.

关键词： Reinforcement learning

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Relief extraction from stone monuments

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IEIE Transactions on Smart Processing and Computing 2018年第4期7卷 321-324页

作者： Heo, Eui-Ju Sa, Jae-Min Choi, Kang-Sun Interdisciplinary Program on Creative Engineering KOREATECH Cheonan Korea Republic of

In this paper, we propose a method to extract reliefs inscribed on stone monuments by analyzing 3-D scan data. Since a relief (carving) is canal-shaped, the curvature-based Frangi filter that has been used in blood vessel detection is suitable for relief extraction. The curvature-based Frangi filter evaluates how well a local surface forms a canal-like curve using principal curvatures. However, for rough surfaces on old and weathered stone monuments, estimated curvatures tend to be noisy, and thus, relief extraction results are degraded. In the proposed relief extraction method, after an initial relief candidate search using curvature-based vesselness estimation, we evaluate the reliability of each relief candidate. Then, for each relief candidate, its vesselness is weighted by the corresponding reliability. As a result, false positives caused by dents and scratches in the relief candidates are successfully alleviated. We confirm that the proposed method extracts reliefs clearly (even from uneven, rough surfaces) and outperforms the conventional curvature-based Frangi filtering method. Copyrights © 2018 The Institute of Electronics and Information Engineers.

关键词： Extraction

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Author Correction: SARS-CoV-2 infection engenders heterogeneous ribonucleoprotein interactions to impede translation elongation in the lungs

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EXPERIMENTAL AND MOLECULAR MEDICINE 2023年第12期55卷 2609-2609页

作者： Kim, Junsoo Youn, Daehwa Choi, Seunghoon Lee, Youn Woo Sumberzul, Dulguun Yoon, Jeongeun Lee, Hanju Bae, Jong Woo Noh, Hyuna On, Dain Hong, Seung-Min An, Se-Hee Jang, Hui Jeong Kim, Seo Yeon Kim, Young Been Hwang, Ji-Yeon Lee, Hyo-Jung Kim, Hong Bin Park, Jun Won Yun, Jun-Won Shin, Jeon-Soo Seo, Jun-Young Nam, Ki Taek Choi, Kang-Seuk Lee, Ho-Young Chang, Hyeshik Seong, Je Kyung Cho, Jun Center for RNA Research Institute for Basic Science (IBS) Seoul National University Seoul Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Seoul Republic of Korea Department of Biomedical Science and Engineering Gwangju Institute of Science and Technology (GIST) Gwangju Republic of Korea Korea Mouse Phenotyping Center (KMPC) Seoul National University Seoul Republic of Korea Laboratory of Developmental Biology and Genomics Research Institute for Veterinary Science and BK 21 PLUS Program for Creative Veterinary Science Research College of Veterinary Medicine Seoul National University Seoul Republic of Korea Department of Nuclear Medicine Seoul National University Bundang Hospital Seongnam Republic of Korea School of Biological Sciences Seoul National University Seoul Republic of Korea Laboratory of Avian Diseases Research Institute for Veterinary Science and BK 21 PLUS Program for Creative Veterinary Science Research College of Veterinary Medicine Seoul National University Seoul Republic of Korea Preclinical Research Center Seoul National University Bundang Hospital Seongnam Republic of Korea Department of Periodontology Section of Dentistry Seoul National University Bundang Hospital Seongnam Republic of Korea Department of Internal Medicine Seoul National University Bundang Hospital Seoul National University College of Medicine Seongnam Republic of Korea Division of Biomedical Convergence College of Biomedical Science Kangwon National University ChunCheon Republic of Korea Laboratory of Veterinary Toxicology College of Veterinary Medicine Seoul National University Seoul Republic of Korea Severance Biomedical Science Institute Graduate School of Medical Science Brain Korea 21 Project Yonsei University College of Medicine Seoul Republic of Korea Department of Nuclear Medicine Seoul National University College of Medicine Seoul Republic of Korea Interdisciplinary Program and BIO MAX Institute Seoul National University

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High-Performance PVC Gel for Adaptive Micro-Lenses with Variable Focal Length

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SCIENTIFIC REPORTS 2017年第1期7卷 2068-2068页

作者： Bae, Jin Woo Shin, Eun-Jae Jeong, Jaeu Choi, Dong-Soo Lee, Jong Eun Nam, Byeong Uk Lin, Liwei Kim, Sang-Youn Department of Mechanical Engineering Berkeley Sensor and Actuator Center University of California Berkeley CA 94720 United States. ATRC Interdisciplinary Program in Creative Engineering Korea University of Technology and Education Cheonan 31253 South Korea. School of Energy Materials and Chemical Engineering Korea University of Technology and Education Chungnam 31253 South Korea. ATRC Interdisciplinary Program in Creative Engineering Korea University of Technology and Education Cheonan 31253 South Korea. sykim@koreatech.ac.kr.

This paper presents a bio-inspired adaptive micro-lens with electrically tunable focus made of nonionic high-molecular-weight polyvinyl chloride (PVC) gel. The optical device mimics the design of the crystalline lens and ciliary muscle of the human eye. It consists of a plano-convex PVC gel micro-lens on Indium Tin Oxide (ITO) glass, confined with an annular electrode operating as an artificial ciliary muscle. Upon electrical activation, the electroactive adhesive force of the PVC gel is exerted on the annular anode electrode, which reduces the sagittal height of the plano-convex PVC gel lens, resulting in focal length variation of the micro-lens. The focal length increases from 3.8 mm to 22.3 mm as the applied field is varied from 200 V/mm to 800 V/mm, comparable to that of the human lens. The device combines excellent optical characteristics with structural simplicity, fast response speed, silent operation, and low power consumption. The results show the PVC gel micro-lens is expected to open up new perspectives on practical tunable optics.

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Author Correction: Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes

Nature cancer

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Nature cancer 2023年 2023 May 19页

作者： Do Young Hyeon Dowoon Nam Youngmin Han Duk Ki Kim Gibeom Kim Daeun Kim Jingi Bae Seunghoon Back Dong-Gi Mun Inamul Hasan Madar Hangyeore Lee Su-Jin Kim Hokeun Kim Sangyeop Hyun Chang Rok Kim Seon Ah Choi Yong Ryoul Kim Juhee Jeong Suwan Jeon Yeon Woong Choo Kyung Bun Lee Wooil Kwon Seunghyuk Choi Taewan Goo Taesung Park Young-Ah Suh Hongbeom Kim Ja-Lok Ku Min-Sik Kim Eunok Paek Daechan Park Keehoon Jung Sung Hee Baek Jin-Young Jang Daehee Hwang Sang-Won Lee School of Biological Sciences Seoul National University Seoul Republic of Korea. Department of Chemistry and Center for Proteogenome Research Korea University Seoul Republic of Korea. Department of Surgery and Cancer Research Institute Seoul National University College of Medicine Seoul Republic of Korea. Department of Anatomy and Cell Biology and Department of Biomedical Sciences Seoul National University College of Medicine Seoul Republic of Korea. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Seoul Republic of Korea. Creative Research Initiatives Center for Epigenetic Code and Diseases Seoul National University Seoul Republic of Korea. Department of Biological Sciences College of Natural Sciences and Department of Molecular Science and Technology Ajou University Suwon Republic of Korea. Department of Pathology Seoul National University College of Medicine Seoul Korea. Department of Computer Science Hanyang University Seoul Republic of Korea. Interdisciplinary Program in Bioinformatics Seoul National University Seoul Republic of Korea. Department of Statistics Seoul National University Seoul Republic of Korea. Korean Cell Line Bank Laboratory of Cell Biology Cancer Research Institute Seoul National University College of Medicine Seoul Korea. Department of New Biology Daegu Gyeongbuk Institute of Science and Technology Daegu Republic of Korea. Department of Biological Sciences College of Natural Sciences and Department of Molecular Science and Technology Ajou University Suwon Republic of Korea. dpark@ajou.ac.kr. Department of Anatomy and Cell Biology and Department of Biomedical Sciences Seoul National University College of Medicine Seoul Republic of Korea. keehoon.jung@snu.ac.kr. Institute of Allergy and Clinical Immunology Seoul National University Medical Research Center Seoul Republic of Korea. keehoon.jung@snu.ac.kr. School of Biological Sciences Seoul National University Seoul Republic of

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Photovoltaic Devices: High Performance Roll‐to‐Roll Produced Fullerene‐Free Organic Photovoltaic Devices via Temperature‐Controlled Slot Die Coating (Adv. Funct. Mater. 6/2019)

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Advanced Functional Materials 2019年第6期29卷

作者： Seok‐In Na You‐Hyun Seo Yoon‐Chae Nah Seok‐Soon Kim Hyojung Heo Jueng‐Eun Kim Nicholas Rolston Reinhold H. Dauskardt Mei Gao Youngu Lee Doojin Vak CSIRO Manufacturing Bag 10 Clayton South Victoria 3168 Australia Professional Graduate School of Flexible and Printable Electronics and Polymer Materials Fusion Research Center Chonbuk National University Deokjin‐dong 664‐14 Jeonju‐si Jeollabuk‐do 561‐756 Republic of Korea Interdisciplinary Program in Creative Engineering School of Energy Materials and Chemical Engineering Korea University of Technology and Education Cheonan 31253 Korea Department of Nano & Chemical Engineering Kunsan National University 290–2 Miryong‐dong Gunsan‐si Jeollabuk‐do 573‐701 Republic of Korea Department of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Korea Department of Applied Physics Stanford University Stanford CA 94305 USA Department of Materials Science and Engineering Stanford University Stanford CA 94305 USA

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Single Cell Genomics: Whole Genome Sequencing of Single Circulating Tumor Cells Isolated by Applying a Pulsed Laser to Cell-Capturing Microstructures (Small 37/2019)

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Small 2019年第37期15卷

作者： Okju Kim Daewon Lee Amos Chungwon Lee Yongju Lee Hyung Jong Bae Han-Byoel Lee Ryong Nam Kim Wonshik Han Sunghoon Kwon Department of Electrical and Computer Engineering Institute of Engineering Research Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Interdisciplinary Program in Bioengineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea BK21+ Creative Research Engineer Development for IT Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Nano Systems Institute Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Department of Surgery Seoul National University College of Medicine 101 Daehak-ro Jongno-gu Seoul 03080 Republic of Korea Biomedical Research Institute Seoul National University Hospital 101 Daehak-ro Jongno-gu Seoul 03080 Republic of Korea Cancer Research Institute Seoul National University 101 Daehak-ro Jongno-gu Seoul 03080 Republic of Korea Institutes of Entrepreneurial BioConvergence Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea Inter-University Semiconductor Research Center 1 Gwanak-ro Gwanak-gu Seoul 08826 Republic of Korea

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