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International Conference on Control, Automation and Systems

作者： Yun-Ki Kim Seung-Hwan Choi Hyun-Woo Kim Jang-Myung Lee Department of Electrical Engineering Pusan National University Department of Interdisciplinary Program in Robotics Pusan National University

ISBN: (纸本)9781467322478

In this paper, PDR system's Improved performance and height estimation are introduced using a low-cost IMU. The personal navigation systems typically have used GPS. But the area where GPS signals are blocked should not be used such as indoor environments. To compensate for this, one of a technique is used PDR system. The location of a pedestrian estimates using only PDR system of the IMU. First of all, in order to estimate the location, a low-cost sensor corrected and manufactured the module. The step is detected using acceleration information by moving of the pedestrian through the module. A step length can be estimated using the detected step. The position estimation and heading will be estimated by the acceleration sensor and gyro sensor. Finally, information of the acceleration sensor and barometer applied to the KF (Kalman Filter) to estimate the height. This paper was tested in a real-environment based on the proposed algorithm. As the result, excellent performance was confirmed within the average distance error within 1% and the position error within 4% in the location estimate. And the results of height estimate, average standard error is confirmed improved performance as max 0.15m in case of using Kalman Filter.

关键词： IMU Pedestrian dead-reckoning Step estimation PDR System Height Estimation

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Estimated force based velocity synchronization for fly touch control in hot rolling process

Estimated force based velocity synchronization for fly touch...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Sung Min Yoon Min Cheol Lee Sung Jin Kim Hyun Hee Kim Keum Gang Cha Graduate School of Mechanical Engineering Pusan National University Kumjeong-ku KR Sch. of Mech. Engeerning Pusan Nat. Unviversity South Korea Interdisciplinary Program in Robotics Pusan National University Kumjeong-ku KR

ISBN: (纸本)9781467391085

In the hot rolling process, scratches are caused by immense friction between the rollers and the steel plate, and this defect reduces the quality of steelworks. To solve this problem, a flying touch method was proposed, which can control the gap between rollers for reducing scratches in hot rolling process. In a flying touch method, it is important that the gap between the rolling rolls can be control precisely and the velocity of rolling rolls can be synchronize to minimize the friction between steel plate and rolling rolls. Therefore, this paper addresses the velocity synchronize control for fly touch method. To reduce friction between steel plate and rolling rolls, this study estimates load torque of rolling rolls using torque estimation method based on SPO and control the velocity of rolling rolls according to estimated load torque. To confirm the performance of the estimated Force based velocity synchronize control, experimental evaluation is performed using down scaled simulator designed in previous study.

关键词： Conferences Mechatronics

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Improved performance of a low-cost PDR system through sensor calibration and analysis

Improved performance of a low-cost PDR system through sensor...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yunki. Kim Donghyuk Lee Kijung. Kim Jangmyung. Lee Dept. of Electrical Engineering Pusan National University Busan Korea Dept. Interdisciplinary Program in Robotics Pusan National University Busan Korea Dept. of Electrical Engineering 'Brain Korea 21 Project’ of Pusan National University Busan Korea

ISBN: (纸本)9781479957378

This paper proposes improvement for performance of a low-cost Pedestrian Dead-Reckoning(PDR) System through calibration and analysis of sensor. It is applied that PDR System for estimating pedestrian's position in the area not being able to be received. also sensor's error is removed by using angle compensation technique and performance of system is improved by analysis of PDR system. Consequently, position of pedestrian is estimated by applying the improved value of sensor and result of angle analysis to PDR system. Experiments were conducted to verify the proposed system. Experimental results within 2% of range error, RMS position error of less than 3% showed superior performance.

关键词： Acceleration Mathematical model Equations Length measurement Temperature sensors Estimation Calibration

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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A study on robust control method of underwater vehicle using SMCSPO

A study on robust control method of underwater vehicle using...

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Asian Control Conference

作者： Hyun Hee Kim Jong Seob Won Hyeon Jin Cho Jun Ho Hwang Min Cheol Lee Interdisciplinary Program in Robotics Pusan National University Geumjeong-gu Busan Korea Department of Mechanical and Automotive Engineering Jeonju University Wansan-gu Jeonju-si Jeollabuk-do Korea Agency for Defense Development Korea School of Mechanical Engineering Pusan National University Geumjeong-gu Busan Korea

ISBN: (纸本)9781509015740;9781509015733

The application of robust control method is required for the design of the automatic control system of the unmanned underwater vehicle which is operated in underwater environment under great disturbance. Sliding Perturbation Observer (SPO) was developed to overcome the chattering phenomenon which is a weak point of the sliding mode control. This control method can be applied to the control of underwater vehicle operating in strong environmental disturbances because it has the advantage of estimating and compensating for nonlinear components, modeling uncertainties and environmental disturbances of the system. In this study, the sliding mode control with sliding perturbation observer (SMCSPO) is simulated in an underwater vehicle to evaluate the disturbance compensation performance and compare it with a PID controller.

关键词： Underwater vehicles Perturbation methods Vehicle dynamics Observers Mathematical model Sliding mode control PI control

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M2FN: Multi-step modality fusion for advertisement image assessment

arXiv

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arXiv 2021年

作者： Park, Kyung-Wha Ha, Jung-Woo Lee, JungHoon Kwon, Sunyoung Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Korea Republic of NAVER AI LAB NAVER CLOVA Statistics and Actuarial Science Soongsil University Korea Republic of School of Biomedical Convergence Engineering Pusan National University Korea Republic of Department of Computer Science and Engineering Seoul National University Korea Republic of Surromind Robotics

Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neural networks for this purpose, these studies have not utilized image-related auxiliary attributes, which include embedded text frequently found in ad images. We, therefore, investigated the influence of these attributes on ad image preferences. First, we analyzed large-scale real-world ad log data and, based on our findings, proposed a novel multi-step modality fusion network (M2FN) that determines advertising images likely to appeal to user preferences. Our method utilizes auxiliary attributes through multiple steps in the network, which include conditional batch normalization-based low-level fusion and attention-based high-level fusion. We verified M2FN on the AVA dataset, which is widely used for aesthetic image assessment, and then demonstrated that M2FN can achieve state-of-the-art performance in preference prediction using a real-world ad dataset with rich auxiliary attributes. © 2021, CC BY-NC-SA.

关键词： Marketing

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Biomimetic evolutionary analysis: Robotically-simulated vertebrates in a predator-prey ecology

Biomimetic evolutionary analysis: Robotically-simulated vert...

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IEEE Symposium on Artificial Life, ALIFE

作者： Nicole Doorly Kira Irving Gianna McArthur Keon Combie Virginia Engel Hassan Sakhtah Elise Stickles Hannah Rosenblum Andres Gutierrez Robert Root Chun Wai Liew John H. Long Mechanical and Aerospace Engineering Department Case Western Reserve University Cleveland OH USA Interdisciplinary Robotics Research Laboratory and the Cognitive Science Program Vassar College Poughkeepsie NY USA Neuroscience Institute Stanford University School of Medicine Stanford CA USA Neuroscience and Behavior Program Vassar College Poughkeepsie NY USA Memorial Sloan Kettering Cancer Care Center New York NY USA Department of Biology Vassar College Poughkeepsie NY USA Biochemistry Program Vassar College Poughkeepsie NY USA College of Medicine Howard University College of Medicine Washington D.C. USA School of Oceanography University of Washington Seattle WA USA Vassar College Poughkeepsie NY USA Department of Mathematics Lafayette College Easton PA USA Computer Science Department Lafayette College Easton PA USA Interdisciplinary Robotics Research Laboratory the Department of Biology and the Cognitive Science Program Vassar College Poughkeepsie NY USA

To test adaptation hypotheses about the evolution of animals, we need information about the behavior of phenotypically-variable individuals in a specific environment. To model behavior of ancient fish-like vertebrates, we previously combined evolutionary robotics and software simulations to create autonomous biomimetic swimmers in a simple aquatic environment competing and foraging for a single source of food. This system allowed us to test the hypothesis that selection for improved forage navigation drove the evolution of stiffer tails. In this paper, we extend our framework to evaluate more complex environments and hypotheses. Specifically, we test the hypothesis that predator-prey dynamics and the need for effective foraging strategies, operating simultaneously, were key selection pressures driving the evolution of morphological and sensory traits in early, fish-like vertebrates. Three evolvable traits were chosen because of their importance in propulsion and predator avoidance: (1) the number of vertebrae in the axial skeleton, (2) the trailing edge span of the caudal fin, and (3) the sensitivity of the sensory lateral line. To produce variable offspring, we used a genetic algorithm that rewarded parents with high fitness, allowing them to mate randomly and combine their mutated gametes. Offspring were then instantiated as autonomous embodied robots, the prey. These prey were chased by a non-evolving autonomous predator. Both kinds of robots were surface swimmers. The prey used a control architecture based on that of living fish: a two-layer subsumption architecture with predator escape over-riding steady swimming during foraging. The performance of six different prey robots in each generation was judged with a relative fitness function that rewarded a combination of high speed, rapid escape acceleration, escape responses, and the ability to stay away from the predator while at the same time staying close to the food source. This approach, which we call biomimet

关键词： Biomimetics Environmental factors Biological system modeling System testing Evolution (biology) Robot sensing systems Animals Navigation Tail Propulsion

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Multi-legged matter transport: A framework for locomotion on noisy landscapes

arXiv

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arXiv 2023年

作者： Chong, Baxi He, Juntao Soto, Daniel Wang, Tianyu Irvine, Daniel Blekherman, Grigoriy Goldman, Daniel I. Interdisciplinary Graduate Program in Quantitative Biosciences Georgia Institute of Technology North Avenue AtlantaGA30332 United States School of Physics Georgia Institute of Technology 837 State St NW AtlantaGA30332 United States Institute for Robotics and Intelligent Machines Georgia Institute of Technology 801 Atlantic Dr NW AtlantaGA30332 United States School of Mathematics Georgia Institute of Technology 686 Cherry St NW AtlantaGA30332 United States

While the transport of matter by wheeled vehicles or legged robots can be guaranteed in engineered landscapes like roads or rails, locomotion prediction in complex environments like collapsed buildings or crop fields remains challenging. Inspired by principles of information transmission which allow signals to be reliably transmitted over noisy channels, we develop a "matter transport" framework demonstrating that non-inertial locomotion can be provably generated over "noisy" rugose landscapes (heterogeneities on the scale of locomotor dimensions). Experiments confirm that sufficient spatial redundancy in the form of serially-connected legged robots leads to reliable transport on such terrain without requiring sensing and control. Further analogies from communication theory coupled to advances in gaits (coding) and sensor-based feedback control (error detection/correction) can lead to agile locomotion in complex terradynamic regimes. © 2023, CC BY.

关键词： Information theory

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On-body non-invasive glucose monitoring sensor based on high figure of merit (FoM) surface plasmonic microwave resonator

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Scientific reports 2023年第1期13卷 17527页

作者： Farzad Soltanian Mehdi Nosrati Saleh Mobayen Chuan-Chun Li Telung Pan Ming-Ta Ke Paweł Skruch Department of Electrical Engineering University of Alberta Edmonton Canada. Department of Electrical Engineering Manhattan College New York USA. Department of Electrical Engineering University of Zanjan Zanjan Iran. mobayens@yuntech.edu.tw. Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliou 640301 Yunlin Taiwan. mobayens@yuntech.edu.tw. National Taiwan University Hospital Yunlin Branch Yunlin Taiwan. a***@***. Bachelor Program in Interdisciplinary Studies College of Future National Yunlin University of Science and Technology Yunlin 64002 Taiwan. Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliou 640301 Yunlin Taiwan. Department of Automatic Control and Robotics AGH University of Science and Technology 30-059 Kraków Poland.

High-figure of merit (FoM) plasmonic microwave resonator is researched as a non-invasive on-body sensor to monitor the human body's blood glucose variation rate in adults for biomedical applications, e.g., diabetic patients. The resonance frequencies of the proposed sensor are measured to be around [Formula: see text] GHz and [Formula: see text] GHz over the frequency band of DC to 6GHz which are suitable for monitoring interstitial fluid (ISF) changing rate. The [Formula: see text] sensor is experimentally wrapped on the human body arm to monitor the blood glucose changing rate via amplitude and frequency variations of the sensor. Amplitude variation and frequency shift are measured to be around 7 dB and 30 MHz, respectively. The measured results demonstrate the high precision of the proposed approach to depict a valid diagram for glucose changing rate due to good impedance matching of the designed microwave sensor and human body. The sensor is shown to enhance the sensitivity by a factor of 5 compared to the conventional ones.

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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