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Possibilities of vehicle state estimation using big data approaches 16

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Possibilities of vehicle state estimation using big data app...

16th Mini Conference on Vehicle System Dynamics, Identification and Anomalies, VSDIA 2018

作者： Fényes, Dániel Németh, Balázs Gáspár, Péter Asszonyi, Máté Systems and Control Laboratory Computer and Automation Research Institute Kende u. 13-17 Budapest Hungary Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Stoczek u. 2 BudapestH-1111 Hungary

Nowadays, the development of the autonomous vehicles is one of the most important challenges for the automotive industry. In general, these vehicles are equipped with numerous sensors, such as onboard-camera, lidar, radar, ultrasonic sensor, accelerometer and gyroscope. These sensors provide information about the environment and other vehicles. This information is not only processed and used directly on the car but also can be stored on internal or cloud-based memory. This collected data might contain hidden information about the motion and the dynamical behaviour of the car. This hidden information can be brought out of the datasets by using big data-based data mining approaches. The aim of the paper is to create a vehicle state estimation model based on the collected sensor data and using data mining tools. In the paper, the sensor data is collected from a high-fidelity simulation software, CarSim. The estimation model is created by the machine-learning software Weka. Finally, the created model is validated through several CarSim simulations. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： computer software

Virtual control Contraction Metrics: Convex Nonlinear Feedback Design via Behavioral Embedding

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arXiv 2020年

作者： Wang, Ruigang Tóth, Roland Koelwijn, Patrick J.W. Manchester, Ian R. Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW2006 Australia Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Systems and Control Lab Institute for Computer Science and Control Budapest Hungary

This paper presents a systematic approach to nonlinear state-feedback control design that has three main advantages: (i) it ensures exponential stability and L2-gain performance with respect to a user-defined set of reference trajectories, and (ii) it provides constructive conditions based on convex optimization and a path-integral-based control realization, and (iii) it is less restrictive than previous similar approaches. In the proposed approach, first a virtual representation of the nonlinear dynamics is constructed for which a behavioral (parameter-varying) embedding is generated. Then, by introducing a virtual control contraction metric, a convex control synthesis formulation is derived. Finally, a control realization with a virtual reference generator is computed, which is guaranteed to achieve exponential stability and L2-gain performance for all trajectories of the targeted reference behavior. We show that the proposed methodology is a unified generalization of the two distinct categories of linear-parameter-varying (LPV) state-feedback control approaches: global and local methods. Moreover, it provides rigorous stability and performance guarantees as a method for nonlinear tracking control, while such properties are not guaranteed for tracking control using standard LPV approaches. © 2020, CC BY.

关键词： Convex optimization

Fully Passive Quantum Key Distribution

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Physical Review Letters 2023年第22期130卷 220801-220801页

作者： Wenyuan Wang Rong Wang Chengqiu Hu Victor Zapatero Li Qian Bing Qi Marcos Curty Hoi-Kwong Lo Department of Physics University of Hong Kong Pokfulam Road Hong Kong Vigo Quantum Communication Center University of Vigo Vigo E-36310 Spain Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo E-36310 Spain AtlanTTic Research Center University of Vigo Vigo E-36310 Spain Department of Electrical and Computer Engineering University of Toronto Toronto Ontario M5S 3G4 Canada Centre for Quantum Information and Quantum Control (CQIQC) University of Toronto Toronto Ontario M5S 1A7 Canada Cisco Systems San Jose California 95134 USA Department of Physics University of Toronto Toronto Ontario M5S 1A7 Canada Quantum Bridge Technologies Inc. 100 College Street Toronto Ontario M5G 1L5 Canada

We propose a fully passive linear optical quantum key distribution (QKD) source that implements both random decoy-state and encoding choices with postselection only, thus eliminating all side channels in active modulators. Our source is general purpose and can be used in, e.g., BB84, the six-state protocol, and reference-frame-independent QKD. It can even potentially be combined with measurement-device-independent QKD to achieve robustness against side channels in both detectors and modulators. We also perform a proof-of-principle experimental source characterization to show its feasibility.

关键词： Optical quantum information processing Quantum communication Quantum cryptography Quantum optics Quantum protocols

Graph attention layer evolves semantic segmentation for road pothole detection: A benchmark and algorithms

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arXiv 2021年

作者： Fan, Rui Wang, Hengli Wang, Yuan Liu, Ming Pitas, Ioannis Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong SAR Hong Kong Industrial R&d Center SmartMore Shenzhen518000 China School of Informatics University of Thessaloniki Thessaloniki541 24 Greece

Existing road pothole detection approaches can be classified as computer vision-based or machine learning-based. The former approaches typically employ 2-D image analysis/ understanding or 3-D point cloud modeling and segmentation algorithms to detect (i.e., recognize and localize) road potholes from vision sensor data, e.g., RGB images and/or depth/disparity images. The latter approaches generally address road pothole detection using convolutional neural networks (CNNs) in an end-to-end manner. However, road potholes are not necessarily ubiquitous and it is challenging to prepare a large wellannotated dataset for CNN training. In this regard, while computer vision-based methods were the mainstream research trend in the past decade, machine learning-based methods were merely discussed. Recently, we published the first stereo visionbased road pothole detection dataset and a novel disparity transformation algorithm, whereby the damaged and undamaged road areas can be highly distinguished. However, there are no benchmarks currently available for state-of-the-art (SoTA) CNNs trained using either disparity images or transformed disparity images. Therefore, in this paper, we first discuss the SoTA CNNs designed for semantic segmentation and evaluate their performance for road pothole detection with extensive experiments. Additionally, inspired by graph neural network (GNN), we propose a novel CNN layer, referred to as graph attention layer (GAL), which can be easily deployed in any existing CNN to optimize image feature representations for semantic segmentation. Our experiments compare GAL-DeepLabv3+, our best-performing implementation, with nine SoTA CNNs on three modalities of training data: RGB images, disparity images, and transformed disparity images. The experimental results suggest that our proposed GAL-DeepLabv3+ achieves the best overall pothole detection accuracy on all training data modalities. The source code, dataset, and benchmark are publicly available at m

关键词： Landforms

An Application for Solving Truth Functions 9th

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An Application for Solving Truth Functions

9th computer Science On-line Conference, CSOC 2020

作者： Pokorný, Pavel Ševčík, Daniel Department of Computer and Communication Systems Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 05 Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 05 Czech Republic

ISBN: (纸本)9783030519643

Nowadays, many technical devices are controlled by logic circuits. These circuits evaluate the situation based on the proposed truth functions, which they then use to perform one of the defined actions. In line with the increasing complexity of individual technical devices, the logic circuits and truth functions are also increasingly complex. For this reason, it makes sense to minimise these functions since they can thereby achieve a simpler technological process and the higher reliability of whole logic systems. This paper describes the Karnaugh Studio application, which resolves the minimisation of these truth functions - and was developed at our faculty (FAI, TBU in Zlín). The minimisation is performed using the Karnaugh Map Method - with support for up to eight variables on input. The application is based on the C++ programming language and the Dear ImGui and Magick++ libraries. Its functionality has been verified on a number of examples. This proved its applicability and ability to be used in the solution of logic circuits in industrial practice. © 2020, Springer Nature Switzerland AG.

关键词： Boolean functions

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary control

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Chinese Journal of Mechanical engineering 2018年第1期31卷 78-99页

作者： Ran Liu Yan-An Yao Wan Ding Xiao-Ping Liu School of Mechanical Electronic and Control EngineeringBeijing Jiaotong University Department of Mechanism Theory and Dynamics of Machines RWTH Aachen University Department of Systems and Computer Engineering Carleton University

Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom(DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of *** control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, *** on a developed genetic algorithm(GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms.

关键词： Tetrahedron-based mobile mechanism Binary control GA Locomotion optimization Manipulation planning

Modified switched IMM estimator based on autoregressive extended Viterbi method for maneuvering target tracking

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Journal of systems engineering and Electronics 2018年第6期29卷 1142-1157页

作者： HADAEGH Mahmoudreza KHALOOZADEH Hamid Department of Electrical & Computer Engineering Science and Research Branch Islamic Azad University Department of Systems and Control K.N.Toosi University of Technology

In this paper, a new approach of maneuvering target tracking algorithm based on the autoregressive extended Viterbi(AREV) model is proposed. In contrast to weakness of traditional constant velocity(CV) and constant acceleration(CA) models to noise effect reduction, the autoregressive(AR) part of the new model which changes the structure of state space equations is proposed. Also using a dynamic form of the state transition matrix leads to improving the rate of convergence and decreasing the noise effects. Since AR will impose the load of overmodeling to the computations, the extended Viterbi(EV) method is incorporated to AR in two cases of EV1 and EV2. According to most probable paths in the interacting multiple model(IMM) during nonmaneuvering and maneuvering parts of estimation, EV1 and EV2 respectively can decrease load of overmodeling computations and improve the AR performance. This new method is coupled with proposed detection schemes for maneuver occurrence and termination as well as for switching initializations. Appropriate design parameter values are derived for the detection schemes of maneuver occurrences and terminations. Finally, simulations demonstrate that the performance of the proposed model is better than the other older linear and also nonlinear algorithms in constant velocity motions and also in various types of maneuvers.

关键词： interacting multiple model(IMM) filter constant acceleration(CA) autoregressive(AR) extended Viterbi(EV) autoregressive extended Viterbi(AREV) extended Kalman filter(EKF)

KartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentation

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arXiv 2021年

作者： Khiarak, Jalil Nourmohammadi Nasab, Samaneh Salehi Jaryani, Farhang Moafinejad, Seyed Naeim Pourmohamad, Rana Amini, Yasin Noshad, Morteza Institute of Control and Computation Engineering Warsaw University of Technology Warsaw Poland School of Engineering Lorestan University Aleshtar Campus Aleshtar Iran Faculty of Engineering Arak University Arak Iran Department of Physics Shahid Beheshti University Tehran Iran School of Computing Informatics and Decision Systems Engineering Arizona State University AZ United States Faculty of Electrical and Computer Engineering University of Kharazmi Iran Stanford University Stanford United States

Iris segmentation and localization in unconstrained environments is challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. To address this problem, we present a U-Net with a pre-trained MobileNetV2 deep neural network method. We employ the pre-trained weights given with MobileNetV2 for the ImageNet dataset and fine-tune it on the iris recognition and localization domain. Further, we have introduced a new dataset, called KartalOl, to better evaluate detectors in iris recognition scenarios. To provide domain adaptation, we fine-tune the MobileNetV2 model on the provided data for NIR-ISL 2021 from the CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa and our dataset. We also augment the data by performing left-right flips, rotation, zoom, and brightness. We chose the binarization threshold for the binary masks by iterating over the images in the provided dataset. The proposed method is tested and trained in CASIA-Iris-Asia, CASIA-Iris-M1, CASIA-Iris-Africa, along the KartalOl dataset. The experimental results highlight that our method surpasses state-of-the-art methods on mobile-based benchmarks. The codes and evaluation results are publicly available at https://***/Jalilnkh/KartalOl-NIR-ISL2021031301. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

State of the Art of Audio- and Video-Based Solutions for AAL

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arXiv 2022年

作者： Aleksic, Slavisa Atanasov, Michael Agius, Jean Calleja Camilleri, Kenneth Čartolovni, Anto Climent-Pérez, Pau Colantonio, Sara Cristina, Stefania Despotovic, Vladimir Ekenel, Hazım Kemal Erakin, Ekrem Florez-Revuelta, Francisco Germanese, Danila Grech, Nicole Sigurðardóttir, Steinunn Gróa Emirzeoğlu, Murat Iliev, Ivo Jovanovic, Mladjan Kampel, Martin Kearns, William Klimczuk, Andrzej Lambrinos, Lambros Lumetzberger, Jennifer Mucha, Wiktor Noiret, Sophie Pajalic, Zada Pérez, Rodrigo Rodriguez Petrova, Galidiya Petrovica, Sintija Pocta, Peter Poli, Angelica Pudane, Mara Spinsante, Susanna Salah, Albert Ali Santofimia, Maria Jose Islind, Anna Sigríður Stoicu-Tivadar, Lacramioara Tellioğlu, Hilda Zgank, Andrej Leipzig University of Applied Sciences Germany TU Wien Austria Department of Anatomy University of Malta Malta Centre for Biomedical Cybernetics Faculty of Engineering Department of Systems and Control Engineering Malta Catholic University of Croatia Croatia Universidad de Alicante Spain Institute of Information Science and Technologies The National Research Council of Italy Italy Department of Systems and Control Engineering University of Malta Malta University of Luxembourg Luxembourg Dept. of Computer Engineering Istanbul Technical University Turkey Reykjavik University School of Computer Science Iceland Sağlık Bilimleri Fakültesi Fizyoterapi ve Rehabilitasyon Karadeniz Technical University Research Information System Turkey TU Sofia Bulgaria Singidunum University Belgrade Serbia University of South Florida United States SGH Warsaw School of Economics Poland Department of Communication and Internet Studies Cyprus University of Technologies Cyprus Technical University of Vienna Austria VID Specialized University Oslo Norway Getafe University Hospital Spain Riga Technical University Latvia University of Zilina Slovakia Università Politecnica Marche Italy Utrecht University Netherlands Universidad de Castilla-La Mancha Spain Reykjavik University Iceland University Politehnica Timisoara Romania University of Maribor Slovenia

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may

关键词： computer vision