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A Vision Based Hardware-Software Real-Time control System for the Autonomous Landing of an UAV 1

International Conference on computer Vision and Graphics, ICCVG 2020

作者： Blachut, Krzysztof Szolc, Hubert Wasala, Mateusz Kryjak, Tomasz Gorgon, Marek Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9783030590062

ISBN: (纸本)9783030590055

In this paper we present a vision based hardware-software control system enabling the autonomous landing of a multirotor unmanned aerial vehicle (UAV). It allows for the detection of a marked landing pad in real-time for a 1280 720 @ 60 fps video stream. In addition, a LiDAR sensor is used to measure the altitude above ground. A heterogeneous Zynq SoC device is used as the computing platform. The solution was tested on a number of sequences and the landing pad was detected with 96% accuracy. This research shows that a reprogrammable heterogeneous computing system is a good solution for UAVs because it enables real-time data stream processing with relatively low energy consumption. © 2020, Springer Nature Switzerland AG.

关键词： System-on-chip

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Flexible control of the Interline DC Power Flow controller Using Virtual Capacitor in VSC-HVDC Grids

Flexible Control of the Interline DC Power Flow Controller U...

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Power Electronic and Drive systems and Technologies Conference (PEDSTC)

作者： Mirhamed Pourmirasghariyan Mirsajed Pourmirasghariyan Seyed Saeid Heidari Yazdi Seyyed Yousef Mousazadeh Mousavi Kumars Rouzbehi G. B. Gharehpetian Departement of Electrical and Computer Engineering Amirkabir University of Technology Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Electrical & Computer Engineering School of Engineering and Digital Science Nazarbayev University Nur-Sultan Kazakhstan Faculty of Engineering and Technology University of Mazandaran Sari Iran Department of Systems and Automatic Control Engineering University of Seville Seville Spain

The performance of Interline DC Power Flow controllers (IDC-PFCs) in Voltage Source Converters (VSC)-based High Voltage Direct Current (HVDC) grids, can be affected due to different issues. The current limitation of HVDC lines, the voltage limitation of HVDC buses, and DC voltage of the IDC-PFC intermediary capacitor prevent effective and efficient operation of IDC-PFCs. In this paper, it is shown that this issue can be overcome by using a virtual capacitor in parallel with the IDC-PFC intermediary capacitor. Also, an energy control-based scheme is proposed for the operation of IDC-PFCs in VSC-HVDC grid. The benefits of using the virtual capacitor are: widening the operational area of the IDC-PFCs for the determined duty cycle and injecting more voltage in series to the interconnected HVDC line to control the related HVDC line current. The proposed solution is successfully evaluated on a CIGRE three-terminal VSC-HVDC grid which is modeled by linearized space-state equations.

关键词： Fluctuations HVDC transmission Capacitors High-voltage techniques Boosting Mathematical models Power conversion

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An Edge Computing System with AMD Xilinx FPGA AI Customer Platform for Advanced Driver Assistance System

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Sensors 2024年第10期24卷 3098页

作者： Chi, Tsun-Kuang Chen, Tsung-Yi Lin, Yu-Chen Lin, Ting-Lan Zhang, Jun-Ting Lu, Cheng-Lin Chen, Shih-Lun Li, Kuo-Chen Abu, Patricia Angela R. Department of Electronic Engineering Chung Yuan Christian University Taoyuan320314 Taiwan Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Information Management Chung Yuan Christian University Taoyuan320317 Taiwan Department of Information Systems and Computer Science Ateneo de Manila University Quezon1108 Philippines

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and efficiency. Following defect detection, the system efficiently transmits detailed information about the type and location of detected defects via the controller Area Network (CAN) interface. This integration of FPGA-based edge computing not only enhances the speed and accuracy of defect detection, but also facilitates real-time communication between the vehicle’s onboard controller and external systems. Moreover, the successful integration of the proposed system transforms ADAS into a sophisticated edge computing device, empowering the vehicle’s onboard controller to make informed decisions in real time. These decisions are aimed at enhancing the overall driving experience by improving safety and performance metrics. The synergy between edge computing and FPGA technology not only advances ADAS capabilities, but also paves the way for future innovations in automotive safety and assistance systems. © 2024 by the authors.

关键词： Deep learning

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing

On the Approximation of the Quotient of Two Gaussian Densiti...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Yanbo Xue Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Career Science Lab Beijing China

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target.

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Secure state estimation over Markov wireless communication channels

Secure state estimation over Markov wireless communication c...

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IEEE Conference on Decision and control

作者： Anastasia Impicciatore Anastasios Tsiamis Yuriy Zacchia Lun Alessandro D’Innocenzo George J. Pappas Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Automatic Control Laboratory ETH Zürich Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA United States

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This note studies state estimation in wireless networked control systems with secrecy against eavesdropping. Specifically, a sensor transmits a system state information to the estimator over a legitimate user link, and an eavesdropper overhears these data over its link independent of the user link. Each connection may be affected by packet losses and is modeled by a finite-state Markov channel (FSMC), an abstraction widely used to design wireless communication systems. This paper presents a novel concept of optimal mean square expected secrecy over FSMCs and delineates the design of a secrecy parameter requiring the user mean square estimation error (MSE) to be bounded and eavesdropper MSE unbounded. We illustrate the developed results on an example of an inverted pendulum on a cart whose parameters are estimated remotely over a wireless link exposed to an eavesdropper.

关键词： Wireless communication Wireless sensor networks Estimation error Networked control systems Channel estimation Packet loss Markov processes

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Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy

arXiv

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arXiv 2023年

作者： Xiao, Jiaren Dai, Quanyu Shen, Xiao Xie, Xiaochen Dai, Jing Lam, James Kwok, Ka-Wai Department of Mechanical Engineering The University of Hong Kong Hong Kong Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science and Technology Hainan University Haikou China Department of Automation Harbin Institute of Technology Shenzhen China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany

Label scarcity in a graph is frequently encountered in real-world applications due to the high cost of data labeling. To this end, semi-supervised domain adaptation (SSDA) on graphs aims to leverage the knowledge of a labeled source graph to aid in node classification on a target graph with limited labels. SSDA tasks need to overcome the domain gap between the source and target graphs. However, to date, this challenging research problem has yet to be formally considered by the existing approaches designed for cross-graph node classification. This paper proposes a novel method called SemiGCL to tackle the graph Semi-supervised domain adaptation with Graph Contrastive Learning and minimax entropy training. SemiGCL generates informative node representations by contrasting the representations learned from a graph’s local and global views. Additionally, SemiGCL is adversarially optimized with the entropy loss of unlabeled target nodes to reduce domain divergence. Experimental results on benchmark datasets demonstrate that SemiGCL outperforms the state-of-the-art baselines on the SSDA tasks. © 2023, CC BY-NC-ND.

关键词： Entropy

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GETAE: Graph Information Enhanced Deep Neural Network Ensemble ArchitecturE for Fake News Detection

arXiv

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arXiv 2024年

作者： Truica, Ciprian-Octavian Apostol, Elena-Simona Marogel, Marius Paschke, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Splaiul Independentei 313 Bucharest060042 Romania Academy of Romanian Scientists Ilfov 3 Bucharest050044 Romania Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 14 Berlin14195 Germany Fraunhofer Institute for Open Communication Systems Kaiserin-Augusta-Allee 31 Berlin10589 Germany

In today’s digital age, fake news has become a major problem that has serious consequences, ranging from social unrest to political upheaval. To address this issue, new methods for detecting and mitigating fake news are required. In this work, we propose to incorporate contextual and network-aware features into the detection process. This involves analyzing not only the content of a news article but also the context in which it was shared and the network of users who shared it, i.e., the information diffusion. Thus, we propose GETAE, Graph Information Enhanced Deep Neural Network Ensemble ArchitecturE for Fake News Detection, a novel ensemble architecture that uses textual content together with the social interactions to improve fake news detection. GETAE contains two Branches: the Text Branch and the Propagation Branch. The Text Branch uses Word and Transformer Embeddings and a Deep Neural Network based on feed-forward and bidirectional Recurrent Neural Networks ([Bi]RNN) for learning novel contextual features and creating a novel Text Content Embedding. The Propagation Branch considers the information propagation within the graph network and proposes a Deep Learning architecture that employs Node Embeddings to create novel Propagation Embedding. GETAE Ensemble combines the two novel embeddings, i.e., Text Content Embedding and Propagation Embedding, to create a novel Propagation-Enhanced Content Embedding which is afterward used for classification. The experimental results obtained on two real-world publicly available datasets, i.e., Twitter15 and Twitter16, prove that using this approach improves fake news detection and outperforms state-of-the-art models. © 2024, CC BY-NC-ND.

关键词： Graph embeddings

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ROSIE: A ROS Adapter for a Modular Digital Twinning Framework

ROSIE: A ROS Adapter for a Modular Digital Twinning Framewor...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Gianmarco Pisanelli Mariusz Tymczuk James A Douthwaite Jonathan M. Aitken James Law Advanced Manufacturing Research Centre The University of Sheffield Sheffield UK Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK Department of Computer Science Advanced Manufacturing Research Centre The University of Sheffield Sheffield UK

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

As robotic systems become more interactive and complex, there is a need to standardise interfaces and simplify development processes. This is particularly pertinent in the field of manufacturing, where human-robot collaboration is on the increase, but where standards and proprietary software are key barriers to deployment and *** this article we present the ROSIE Adapter, a general-purpose, modular adapter developed in ROS designed to support the creation and connection of industry-ready digital twins. Together with our previous work on the modular CSI digital-twin framework, we demonstrate how the ROSIE Adapter creates a versatile "plug-and-play" interface that simplifies the development of new robotic processes, and improves accessibility to novice users. Furthermore, the adaptor supports integration of intuitive interface devices, such as speech and augmented reality interfaces, which enable more natural collaboration. We describe the adaptor and its use in two real-world applications, demonstrate the ease of use via a three-day hackathon event, and provide results showing the faithfulness of the arising digital twins to their connected physical systems.

关键词： Adaptation models Collaboration Process control Data models Digital twins Safety Speech processing

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Do We Run Large-scale Multi-Robot systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling

arXiv

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arXiv 2023年

作者： Kuckling, Jonas Luckey, Robin Avrutin, Viktor Vardy, Andrew Reina, Andreagiovanni Hamann, Heiko The Department of Computer and Information Science University of Konstanz Konstanz78457 Germany The Centre for the Advanced Study of Collective Behaviour University of Konstanz Germany The Institute of Computer Engineering University of Lübeck Lübeck Germany The Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany The Department of Computer Science The Department of Electrical and Computer Engineering Memorial University of Newfoundland St. John's Canada IRIDIA Université Libre de Bruxelles Brussels Belgium

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing behavior, a strict decentralized approach, and limiting the robot-robot communication. Despite applying such strategies, any multi-robot system breaks above a certain critical system size (i.e., number of robots) as too many robots share a resource (e.g., space, communication channel). We provide additional evidence based on simulations, that at these critical system sizes, the system performance separates into two phases: nearly optimal and minimal performance. We speculate that in real-world applications that are configured for optimal system size, the supposedly high-performing system may actually live on borrowed time as it is on a transient to breakdown. We provide two modeling options (based on queueing theory and a population model) that may help to support this reasoning. © 2023, CC BY.

关键词： Multipurpose robots

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Preface

Lecture Notes in Electrical Engineering

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Lecture Notes in Electrical Engineering 2024年 1114 LNEE卷 v页

作者： Lin, Jerry Chun-Wei Shieh, Chin-Shiuh Horng, Mong-Fong Chu, Shu-Chuan Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and IT Devices Silesian University of Technology Gliwice Poland

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