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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Luis Piardi André Oliveira Pedro Costa Paulo Leitão Research Center in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba-PR Brazil Technology and Science (INESC TEC) Institute for Systems and Computer Engineering Porto Portugal Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Cyber-physical systems (CPS) rapidly expand within industrial contexts in a new era of digitalization, processing power, and inter-device communication capabilities. These advancements integrate technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud and edge computing, granting processes and operations a high degree of autonomy. In addition, these interconnections foster collective intelligence arising from information exchange and collaboration between components, often outperforming individual capabilities. This collective intelligence manifests in fault detection and diagnosis (FDD) tasks within CPS, as it significantly improves the flexibility, performance, and scalability. However, the inherent complexity of CPS poses challenges in determining the best configuration of the collaboration parameters, such as when and how to collaborate, wherein incorrect adjustments may lead to decision errors and compromise the system's performance. With this in mind, this paper proposes seven metrics to evaluate collaboration performance for fault detection and diagnosis in multi-agent systems (MAS)-based CPS, evaluating when the collaboration is beneficial or when the collaboration parameters need to be adjusted. The experiments focus on collaborative fault detection in temperature and humidity sensors within warehouse racks, where the proposed evaluation metrics point out the impact of collaboration on the detection task, as well as possible actions to be adopted to improve the agent's performance.

关键词： Measurement Temperature sensors Fault detection System performance Collaboration Cyber-physical systems Collective intelligence Sensors Internet of Things Artificial intelligence

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A low-cost device-based data approach to Eight Hop Test

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Procedia computer science 2025年 256卷 1135-1142页

作者： Luís Pimenta Paulo Jorge Coelho Norberto Jorge Gonçalves José Paulo Lousado Carlos Albuquerque Nuno M. Garcia Eftim Zdravevski Petre Lameski Ivan Miguel Pires Escola de Ciências e Tecnologia University of Trás-os-Montes e Alto Douro Vila Real Portugal Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Research Centre in Digital Services (CISeD) Polytechnic Institute of Viseu Portugal Health Sciences Research Unit: Nursing (UICISA: E) Nursing School of Coimbra (ESEnfC) Coimbra Portugal Higher School of Health Polytechnic Institute of Viseu Viseu Portugal Child Studies Research Center (CIEC) University of Minho Braga Portugal Institute of Biophysics and Biomedical Engineering (IBEB) Faculty of Sciences University of Lisbon Lisbon Portugal Faculty of Computer Science and Engineering University Ss Cyril and Methodius Skopje Macedonia Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

The Eight Hop Test is a physical rehabilitation exercise involving jumping with one leg in a circuit similar to the number eight. This study aims to analyze data related to the performance of the test, relating it to gender and pathologies in the population. A mobile application was implemented to acquire accelerometer data, which was then analyzed using various artificial intelligence methods. The study found reliable accuracy in identifying participants’ gender (60%) and specific pathologies (50%), suggesting that mobile sensors can effectively support medical evaluations. Neural Network showed the highest accuracy for multivariate data, while the k-Nearest Neighbor was most effective for binary classifications. The mobile device-based method helps healthcare professionals measure physical strength evolution in lower limb injuries and predicts pathologies with near-100% accuracy using machine learning methods. Future research will explore more individuals and data to improve healthcare treatments and explore new techniques and analyses.

关键词： Eight Hop Test machine learning accelerometer diseases gender

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Biomimetic robots promote the 3Rs Principle in animal testing

Biomimetic robots promote the 3Rs Principle in animal testin...

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2021 Conference on Artificial Life, ALIFE 2021

作者： Bierbach, David Francisco, Fritz Lukas, Juliane Landgraf, Tim Maxeiner, Moritz Romanczuk, Pawel Musiolek, Lea Hafner, Verena V. Krause, Jens Faculty of Life Sciences Division of Biology and Ecology of Fishes Humboldt Universität zu Berlin Berlin Germany Department of Biology and Ecology of Fishes Leibniz Institute of Freshwater Ecology and Inland Fisheries Berlin Germany Dahlem Center for Machine Learning and Robotics Freie Universität Berlin Berlin Germany Faculty of Life Sciences Institute for Theoretical Biology Humboldt Universität zu Berlin Berlin Germany Adaptive Systems Group Department of Computer Science Humboldt-Universität zu Berlin Berlin Germany

In order to strengthen animal welfare, many countries require that experimenters follow the ‘3Rs Principle’ when designing animal experiments. The 3Rs call for a reduction in the number of animals used, the refinement of methods to reduce stress as well as the full replacement of animals in experimentation through alternative methods. Biomimetic robots that resemble live animals and allow for natural-like interactions represent a valuable tool to achieve the 3Rs’ objectives. On the basis of our research with a robotic fish that is accepted as a conspecific by live poeciliid fishes, we highlight how biomimetic robots can reduce the number of animals tested by (a) substituting live animals, (b) providing highly standardized cues, and (c) reducing overall stress for live animals during tests through less handling. © 2021 ALIFE. All Rights Reserved.

关键词： Invertebrates

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Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets

Creating Own AI Datasets from Different Language Sources Eff...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： György Molnár József Cserkó Enikő Nagy Zoltán Balogh Kandó Kálmán Faculty of Electrical Engineering Óbuda University Budapest Hungary János Csere Apáczai Faculty Széchenyi University Győr Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Széchenyi University Doctoral School of Multidisciplinary Engineering Sciences (MMTDI) Győr Hungary Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Institute of Cyberphysical Systems Óbuda University Budapest Hungary Department of Informatics Faculty of Natural Sciences and Informatics Constantine the Philosopher University in Nitra Nitra Slovakia

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation.

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Efficient Visual Perception of Human-Robot Walking Environments Using Semi-Supervised Learning

Efficient Visual Perception of Human-Robot Walking Environme...

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

作者： Dmytro Kuzmenko Oleksii Tsepa Andrew Garrett Kurbis Alex Mihailidis Brokoslaw Laschowski Department of Mathematics National University of Kyiv-Mohyla Academy Kyiv Ukraine Department of Mathematical Methods of System Analysis Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Department of Computer Science University of Toronto Toronto Canada Department of Systems Design Engineering University of Waterloo Waterloo Canada Temerty Faculty of Medicine University of Toronto Toronto Canada Institute of Biomedical Engineering University of Toronto Toronto Canada Toronto Rehabilitation Institute Toronto Canada Department of Mechanical and Industrial Engineering Robotics Institute University of Toronto Toronto Canada

Convolutional neural networks trained using supervised learning can improve visual perception for human-robot walking. These advances have been possible due to largescale datasets like ExoNet and StairNet - the largest open-source image datasets of real-world walking environments. However, these datasets require vast amounts of manually annotated data, the development of which is time consuming and labor intensive. Here we present a novel semi-supervised learning system (ExoNet-SSL) that uses over 1.2 million unlabelled images from ExoNet to improve training efficiency. We developed a deep learning model based on mobile vision transformers and trained the model using semi-supervised learning for image classification. Compared to standard supervised learning (98.4%), our ExoNet-SSL system was able to maintain high prediction accuracy (98.8%) when tested on previously unseen environments, while requiring 35% fewer labelled images during training. These results show that semi-supervised learning can improve training efficiency by leveraging large amounts of unlabelled data and minimize the size requirements for manually annotated images. Future research $\text{will}$ focus on model deployment for onboard real-time inference and control of human-robot walking.

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Continuous-time fitted value iteration for robust policies

arXiv

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arXiv 2021年

作者： Lutter, Michael Belousov, Boris Mannor, Shie Fox, Dieter Garg, Animesh Peters, Jan Intelligent Autonomous Systems group Computer Science Department Technical University of Darmstadt Darmstadt Germany Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion – Israel Institute of Technology and a Distinguished Scientist at NVIDIA Tel Aviv Israel Allen School of Computer Science & Engineering University of Washington and Senior Director of Robotics Research NVIDIA Washington Seattle United States Computer Science Department University of Toronto NVIDIA Toronto Canada

Solving the Hamilton-Jacobi-Bellman equation is important in many domains including control, robotics and economics. Especially for continuous control, solving this differential equation and its extension the Hamilton-Jacobi-Isaacs equation, is important as it yields the optimal policy that achieves the maximum reward on a give task. In the case of the Hamilton-Jacobi-Isaacs equation, which includes an adversary controlling the environment and minimizing the reward, the obtained policy is also robust to perturbations of the dynamics. In this paper we propose continuous fitted value iteration (cFVI) and robust fitted value iteration (rFVI). These algorithms leverage the non-linear control-affine dynamics and separable state and action reward of many continuous control problems to derive the optimal policy and optimal adversary in closed form. This analytic expression simplifies the differential equations and enables us to solve for the optimal value function using value iteration for continuous actions and states as well as the adversarial case. Notably, the resulting algorithms do not require discretization of states or actions. We apply the resulting algorithms to the Furuta pendulum and cartpole. We show that both algorithms obtain the optimal policy. The robustness Sim2real experiments on the physical systems show that the policies successfully achieve the task in the real-world. When changing the masses of the pendulum, we observe that robust value iteration is more robust compared to deep reinforcement learning algorithm and the non-robust version of the algorithm. Videos of the experiments are shown at https://***/view/rfvi Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamic programming

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Offsite Evaluation of Localization systems: Criteria, systems, and Results From IPIN 2021 and 2022 Competitions

IEEE Journal on Indoor and Seamless Positioning and Navigati...

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IEEE Journal on Indoor and Seamless Positioning and Navigation 2024年 2卷 92-129页

作者： Potorti, Francesco Crivello, Antonino Lee, Soyeon Vladimirov, Blagovest Park, Sangjoon Chen, Yushi Wang, Long Chen, Runze Zhao, Fang Zhuge, Yue Luo, Haiyong Perez-Navarro, Antoni Jimenez, Antonio R. Wang, Han Liang, Hengyi De Cock, Cedric Plets, David Cui, Yan Xiong, Zhi Li, Xiaodong Ding, Yiming Franco, Fernando Javier Alvarez Polo, Fernando Jesus Aranda Rodriguez, Felipe Parralejo Moreira, Adriano Pendao, Cristiano Silva, Ivo Ortiz, Miguel Zhu, Ni Li, Ziyou Renaudin, Valerie Wei, Dongyan Ji, Xinchun Zhang, Wenchao Wang, Yan Ding, Longyang Kuang, Jian Zhang, Xiaobing Dou, Zhi Yang, Chaoqun Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Coene, Sander Li, Chenglong Venus, Alexander Leitinger, Erik Tertinek, Stefan Witrisal, Klaus Wang, Yi Wang, Shaobo Jin, Beihong Zhang, Fusang Su, Chang Wang, Zhi Li, Siheng Li, Xiaodong Li, Shitao Pan, Mengguan Zheng, Wang Luo, Kai Ma, Ziyao Gao, Yanbiao Chang, Jiaxing Ren, Hailong Guo, Wenfang Torres-Sospedra, Joaquin Pisa56124 Italy Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing100876 China Chinese Academy of Sciences Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Beijing100190 China Universitat Oberta de Catalunya Faculty of Computer Sciences Multimedia and Telecommunication Barcelona08035 Spain Arganda del Rey28500 Spain Huawei Technologies Company Ltd. Shenzhen100015 China IMEC-WAVES/Ghent University Department of Information Technology Gent9052 Belgium Nanjing University of Aeronautics and Astronautics College of Automation Nanjing210016 China University of Extremadura Badajoz06006 Spain University of Trás-os-Montes and Alto Douro Department of Engineering School of Sciences and Technology Vila Real5000-801 Portugal Universidade Do Minho Centro Algoritmi Guimarães4800-058 Portugal Ame Department of the University Gustave Eiffel Geoloc Laboratory Bouguenais44344 France Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Wuhan University Gnss Research Center Wuhan430072 China AutoNavi Software Company Ltd. China Fraunhofer Institute for Integrated Circuits Iis Fraunhofer Iis Nuremberg90411 Germany Erlangen91058 Germany Graz University of Technology Christian Doppler Laboratory for Location-Aware Electronic Systems Graz8010 Austria Institute of Software Chinese Academy of Sciences Beijing100190 China Purple Mountain Laboratories Pervasive Communication Research Center Nanjing210000 China Beijing University of Posts and Telecommunications Beijing100876 China

Indoor positioning is a thriving research area, which is slowly gaining market momentum. Its applications are mostly customized, ad hoc installations;ubiquitous applications analogous to Global Navigation Satellite System for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the indoor positioning and indoor navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site tracks. In contrast with on-site tracks where competitors bring their systems on-site - which were impossible to organize during 2021 and 2022 - in off-site tracks competitors download prerecorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem. © 2023 CCBY.

关键词： Smartphones

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Clustering of the Blendshape facial model

arXiv

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arXiv 2021年

作者： Racković, Stevo Soares, Cláudia Jakovetić, Dušan Desnica, Zoranka Ljubobratović, Relja Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal Computer Science Department NOVA School of Science and Technology Lisbon Portugal Department of Mathematics Faculty of Sciences UNS Novi Sad Serbia 3Lateral Epic Games Company

Digital human animation relies on high-quality 3D models of the human face—rigs. A face rig must be accurate and, at the same time, fast to compute. One of the most common rigging models is the blendshape model. We present a novel approach for learning the inverse rig parameters at increased accuracy and decreased computational cost at the same time. It is based on a two fold clustering of the blendshape face model. Our method focuses exclusively on the underlying space of deformation and produces clusters in both the mesh space and the controller space—something that was not investigated in previous literature. This segmentation finds intuitive and meaningful connections between groups of vertices on the face and deformation controls, and further these segments can be observed independently. A separate model for solving the inverse rig problem is then learnt for each segment. Our method is completely unsupervised and highly parallelizable. © 2021, CC BY-NC-SA.

关键词： Deformation

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14th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2020

作者： Pérez-Pérez, Martín Lourenço, Anália Igrejas, Gilberto Fdez-Riverola, Florentino ESEI Department of Computer Science University of Vigo Edificio Politécnico Campus Universitario as Lagoas s/n 32004 Ourense Spain CINBIO The Biomedical Research Centre University of Vigo Campus Univesitario Lagoas-Marcosende Vigo36310 Spain SING Next Generation Computer Systems Group Galicia Sur Health Research Institute SERGAS-UVIGO Vigo Spain CEB Centre of Biological Engineering University of Minho Campus de Gualtar Braga4710-057 Portugal Department of Genetics and Biotechnology University of Trás-os-Montes and Alto Douro Vila Real Portugal Functional Genomics and Proteomics Unit University of Trás-os-Montes and Alto Douro Vila Real Portugal LAQV-REQUIMTE Faculty of Science and Technology Nova University of Lisbon Lisbon Portugal

ISBN: (纸本)9783030545673

Concerning the field of Health sciences, one of the trends with the greatest impact today is related to the feeding and consumption of foods intended for chronic patients with a nutritional association. According to this, the gluten-free diet is one of the diets with a today’s fastest-growing due to their health therapy associations for different diseases and because of more and more people are freely choosing to follow a gluten-free diet. On this subject, e-commerce platforms are destined to be a key point for the sale of this kind of products due to: (i) the change in the business model caused by the electronic platforms and (ii) the expected increase consumption of disease designed special foods. For this reason, the experiences written by chronic disease patients and consumers in these platforms have become increasingly relevant. In this sense, the present work applies biomedical text mining methods and demographic knowledge inference techniques to a large number of gluten-free foods consumer’s experiences to discover a wide range of health-related topics associated to gluten-free products, alimentary social trends and demographics differences. The results of these analyses show significant trends over time;differences between males and females consumption and a wide range of health-related conclusions, such as: why consumers start a free gluten diet or what are the most discussed diseases and adverse reactions related to these products. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Nutrition

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Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

arXiv

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： robotics

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