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18th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2018

作者： Ma, Jun Chen, Si-Lu Liang, Wenyu Teo, Chek Sing Tay, Arthur Al Mamun, Abdullah Tan, Kok Kiong SIMTech-NUS Joint Lab. on Precision Motion Systems Department of Electrical and Computer Engineering National University of Singapore Singapore117582 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Agency for Science Technology and Research Singapore Institute of Manufacturing Technology Singapore138634 Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo Zhejiang315201 China

ISBN: (纸本)9780995775121

Dual-drive H-gantry is widely used in many industrial processes that require high-speed and high-precision Cartesian motion. Unlike the rigid-linked gantry design, the flexure-linked design is able to prevent the damage of the cross-arm because a small degree of rotation angle is possible. However, the flexure-linked design may induce the resonant modes of the gantry because of high frequency control signals. To maintain the precision tracking of two carriages and minimize the chattering of control efforts, we aim to seek the most suitable flexure joints among the available ones while optimizing the decentralized feedback controller parameters under model uncertainties. In this way, good tracking performance is achieved without costly system re-design. In this work, we formulate the mechatronic design problem as an H2 guaranteed cost control problem. All the stabilizing feedback controller gains are parameterized over a convex set, and the global optimum is obtained by means of an outer-linearization-based algorithm. Experiments are conducted and the results successfully validate the effectiveness of the proposed design approach. © 2018 CURRAN-CONFERENCE. All rights reserved.

关键词： Convex optimization Dual-drive H-gantry Flexure Mechatronic design Optimal control Parallel mechanism

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Pull message passing for nonparametric belief propagation

arXiv

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arXiv 2018年

作者： Desingh, Karthik Opipari, Anthony Jenkins, Odest Chadwicke Laboratory for Perception RObotics Grounded REasoning SystemS Department of Electrical Engineering and Computer Science Robotics Institute University of Michigan Ann ArborMI48105 United States

We present a "pull" approach to approximate products of Gaussian mixtures within message updates for Nonparametric Belief Propagation (NBP) inference. Existing NBP methods often represent messages between continuous-valued latent variables as Gaussian mixture models. To avoid computational intractability in loopy graphs, NBP necessitates an approximation of the product of such mixtures. Sampling-based product approximations have shown effectiveness for NBP inference. However, such approximations used within the traditional "push" message update procedures quickly become computationally prohibitive for multi-modal distributions over high-dimensional variables. In contrast, we propose a "pull" method, as the Pull Message Passing for Nonparametric Belief propagation (PMPNBP) algorithm, and demonstrate its viability for efficient inference. We report results using an experiment from an existing NBP method, PAMPAS, for inferring the pose of an articulated structure in clutter. Results from this illustrative problem found PMPNBP has a greater ability to efficiently scale the number of components in its mixtures and, consequently, improve inference accuracy. Copyright © 2018, The Authors. All rights reserved.

关键词： Message passing

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Single-phasing protection of line-operated motors of different efficiency classes 53

Single-phasing protection of line-operated motors of differe...

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53rd IEEE/IAS Industrial and Commercial Power systems Technical Conference, I and CPS 2017

作者： Ferreira, Au Silva, Au De Almeida, Au Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Polo II Portugal

ISBN: (纸本)9781509057245

Single-phasing is one of the major causes of motor failure in the industry. The electric motor market is changing fast due to the minimum energy performance standards. In a large number of cases, particularly when the original old motors are retrofitted with motors of higher efficiency classes, the respective overload protection devices are not properly tuned/configured or upgraded/replaced. In this paper, an overview of the motor protective devices and the main results of an experimental study on the behavior of five three-phase 7.5-kW, 400-V, 50-Hz, 4-pole motors, namely, four squirrel-cage induction motors of IE1, IE2/EPAct, IE3/NEMA Premium and IE4 classes and one line-start permanent-magnet of IE4 class, under single-phasing supply at no-load, locked-rotor and part-load operation, are presented. On the basis of the obtained results, it can be concluded that, in general, modern commercial thermal overload relays or thermal-magnetic circuit-breakers are able to protect line-operated motors against single-phasing operation, tripping within a safe time window, as long as they have differential mode mechanism, their trip class is properly selected, and the current setting correctly adjusted as a function of the motor efficiency class, technology, service factor, load, rated power and rated current. © 2017 IEEE.

关键词： Magnetic circuits

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Robot Force Control on a Beating Heart

Robot Force Control on a Beating Heart

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作者： Cortesão, Rui Dominici, Michel Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra3030 Portugal Institute of Systems and Robotics University of Coimbra Coimbra3030 Portugal

Cardiac interventions have to deal with several difficulties, where heart motion is a major one. This paper addresses the heart motion compensation problem under contact, relying on robot force control techniques. A double active observer (AOB) architecture is proposed to tackle precise force control in the presence of heart motion. One AOB controls the desired interaction force, and the other one is responsible for compensating heart motion autonomously. Three-degrees of freedom (DOF) force tracking on top of a beating heart is presented, showing that with the proposed control architecture, it is possible to have force controlled interventions with root mean square errors below 0.56 N (based on raw data). The 4-DOF whole arm manipulator (WAM) from Barrett Technologies is the medical arm, while another 3-DOF robot carrying an ex vivo heart generates heart motion based on recorded biosignals. © 2017 IEEE.

关键词： Force control

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Shape reconstruction using a mobile robot for demining and UXO classification

Shape reconstruction using a mobile robot for demining and U...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Dogru, Sedat Marques, Lino Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3030-290 Portugal

ISBN: (纸本)9781509046331

Metal detectors are widely used to detect and localize land mines, as well as metallic clutter that causes many false alarms. These false alarms are handled by manual inspection with a prodder or using extra features like size and depth as well as fusion with other sensors like ground penetrating radar or chemical sensors. Directly shape itself has never been used, mainly due to infeasibility of the results of the few existing studies, which require controlled environments and dense sampling of the target objects. In this paper, we propose a new method for shape reconstruction that works with sparse data, and show its feasibility using field data collected by a mobile robot equipped with a commercial pulse induction metal detector carried by a custom 2DoF arm. This paper also describes the method employed to sweep natural terrains with the mobile manipulator and provides results of imaging a set of different metallic objects. © 2017 IEEE.

关键词： Mobile robots

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Forecasting intracranial hypertension using multi-scale waveform metrics

arXiv

引用

arXiv 2019年

作者： Hüser, Matthias Kündig, Adrian Karlen, Walter De Luca, Valeria Jaggi, Martin Biomedical Informatics Group Department of Computer Science ETH Zürich Universitätstrasse 6 Zürich8092 Switzerland Mobile Health Systems Lab Institute of Robotics and Intelligent Systems Department of Health Sciences and Technology ETH Zürich Zürich8008 Switzerland Department of Information Technology and Electrical Engineering ETH Zürich Zürich8092 Switzerland Machine Learning & Optimization Lab EPFL Lausanne1015 Switzerland

Objective: Acute intracranial hypertension is an important risk factor of secondary brain damage after traumatic brain injury. Hypertensive episodes are often diagnosed reactively, leading to late detection and lost time for intervention planning. A pro-active approach that predicts critical events several hours ahead of time could assist in directing attention to patients at risk. Approach: We developed a prediction framework that forecasts onsets of acute intracranial hypertension in the next 8 hours. It jointly uses cerebral auto-regulation indices, spectral energies and morphological pulse metrics to describe the neurological state of the patient. One-minute base windows were compressed by computing signal metrics, and then stored in a multi-scale history, from which physiological features were derived. Main results: Our model predicted events up to 8 hours in advance with alarm recall rates of 90% at a precision of 30.3% in the MIMIC-III waveform database, improving upon two baselines from the literature. We found that features derived from high-frequency waveforms substantially improved the prediction performance over simple statistical summaries of low-frequency time serie1s, and each of the three feature classes contributed to the performance gain. The inclusion of long-term history up to 8 hours was especially important. Significance: Our results highlight the importance of information contained in high-frequency waveforms in the neurological intensive care unit. They could motivate future studies on pre-hypertensive patterns and the design of new alarm algorithms for critical events in the injured brain. Copyright © 2019, The Authors. All rights reserved.

关键词： Morphology

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

引用

arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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A Scalable Deep Attention Mechanism of Instance Segmentation for the Investigation of Chromosome

引用

SLAS technology 2025年 100306页

作者： Neelam Umbreen Sara Ali Hasan Sajid Yasar Ayaz Shrooq Alsenan Yunyoung Nam So Yeon Kim Muhammad Baber Sial National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: neelamumbreen.phd@smme.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan Suzhou Industrial Park (SIP) Monash Research Institute of Science and Technology Monash University 8Q9C+R6W Suzhou Jiangsu China. School of Mechanical and Manufacturing Engineering (SMME) National University of Sciences and Technology (NUST) Islamabad NUST-COVENTRY Human-Robot Interaction (NC-HRI) Laboratory Pakistan Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: sarababer@smme.nust.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: hasan.sajid@smme.nust.edu.pk. Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: yasar@smme.nust.edu.pk. Information Systems Department College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia. Electronic address: shalsenan@pnu.edu.sa. Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang University Asan 31538 Korea. Electronic address: ynam@sch.ac.kr. Department of Artificial Intelligence Department of Software and Computer Engineering Ajou University. Electronic address: jebi1771@ajou.ac.kr. School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China. Electronic address: babersial@***.

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variability in chromosome shapes, and the scarcity of high-quality annotated datasets. This study proposes a robust instance segmentation framework that integrates an automated annotation pipeline with an enhanced deep learning architecture to address these challenges. A novel dataset is introduced, comprising metaphase images and corresponding karyograms, annotated with precise instance segmentation information across 24 chromosome classes in COCO format. To overcome the labor-intensive manual annotation process, a feature-based image registration technique leveraging SIFT and homography is employed, enabling the accurate mapping of chromosomes from karyograms to metaphase images and significantly improving annotation quality and segmentation performance. The proposed framework includes a custom Mask R-CNN model enhanced with an Attention-based Feature Pyramid Network (AttFPN), spatial attention mechanisms, and a LastLevelMaxPool block for superior multi-scale feature extraction and focused attention on critical regions of the image. Experimental evaluations demonstrate the model's efficacy, achieving a mean average precision (mAP) of 0.579 at IoU = 0.50:0.95, surpassing the baseline Mask R-CNN and Mask R-CNN with AttFPN by 3.94% and 5.97% improvements in mAP and AP50, respectively. Notably, the proposed architecture excels in segmenting small and medium-sized chromosomes, addressing key limitations of existing methods. This research not only introduces a state-of-the-art segmentation framework but also provides a benchmark dataset, setting a new standard for chromosome instance segmentation in biomedical imaging. The integration of automated dataset creation with advanced model design offers a scalable and transferable solution, paving the way for tackling similar challenges in other domains of biomedical and cytogenetic imagi

关键词： Chromosome segmentation Instance segmentation, cytogenetics Mask R-CNN attention mechanism biomedical imaging multi-scale feature fusion

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An overview of perception methods for horticultural robots: From pollination to harvest

arXiv

引用

arXiv 2018年

作者： Ahn, Ho Seok Dayoub, Feras Popović, Marija MacDonald, Bruce A. Siegwart, Roland Sa, Inkyu Department of Electrical and Computer Engineering CARES University of Auckland 368 Khyber Pass Rd Newmarket Auckland1023 New Zealand Department of Mechanical and Process Engineering Institute of Robotics and Intelligent Systems Autonomous Systems Lab. ETH Zurich Switzerland

Horticultural enterprises are becoming more sophisticated as the range of the crops they target expands. Requirements for enhanced efficiency and productivity have driven the demand for automating on-field operations. However, various problems remain yet to be solved for their reliable, safe deployment in real-world scenarios. This paper examines major research trends and current challenges in horticultural robotics. Specifically, our work focuses on sensing and perception in the three main horticultural procedures: Pollination, yield estimation, and harvesting. For each task, we expose major issues arising from the unstructured, cluttered, and rugged nature of field environments, including variable lighting conditions and difficulties in fruit-specific detection, and highlight promising contemporary studies. Based on our survey, we address new perspectives and discuss future development trends. Copyright © 2018, The Authors. All rights reserved.

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Human intention estimation based on hidden Markov model motion validation for safe flexible robotized warehouses

arXiv

引用

arXiv 2018年

作者： Petković, Tomislav Puljiz, David Marković, Ivan Hein, Björn University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics Unska 3 ZagrebHR-10000 Croatia Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Intelligent Process Automation and Robotics Lab Kaiserstraße 12 Deutschland KarlsruheDE-76131

With the substantial growth of logistics businesses the need for larger warehouses and their automation arises, thus using robots as assistants to human workers is becoming a priority. In order to operate efficiently and safely, robot assistants or the supervising system should recognize human intentions in real-time. Theory of mind (ToM) is an intuitive human conception of other humans' mental state, i.e., beliefs and desires, and how they cause behavior. In this paper we propose a ToM based human intention estimation algorithm for flexible robotized warehouses. We observe human's, i.e., worker's motion and validate it with respect to the goal locations using generalized Voronoi diagram based path planning. These observations are then processed by the proposed hidden Markov model framework which estimates worker intentions in an online manner, capable of handling changing environments. To test the proposed intention estimation we ran experiments in a real-world laboratory warehouse with a worker wearing Microsoft Hololens augmented reality glasses. Furthermore, in order to demonstrate the scalability of the approach to larger warehouses, we propose to use virtual reality digital warehouse twins in order to realistically simulate worker behavior. We conducted intention estimation experiments in the larger warehouse digital twin with up to 24 running robots. We demonstrate that the proposed framework estimates warehouse worker intentions precisely and in the end we discuss the experimental results. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality

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