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Joint Vision-Based Navigation, control and Obstacle Avoidance for UAVs in Dynamic Environments

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arXiv 2019年

作者： Potena, Ciro Nardi, Daniele Pretto, Alberto Department of Computer Control Management Engineering Sapienza University of Rome Italy IT+Robotics S.r.l. Vicenza Italy

This work addresses the problem of coupling vision-based navigation systems for Unmanned Aerial Vehicles (UAVs) with robust obstacle avoidance capabilities. The former is formulated by a maximization of the point of interest visibility, while the latter is modeled by ellipsoidal repulsive areas. The whole problem is transcribed into an Optimal control Problem (OCP), and solved in a few milliseconds by leveraging state-of-the-art numerical optimization. The resulting trajectories are then well suited to achieve the specified goal location while avoiding obstacles by a safety margin and minimizing the probability to loose track with the target of interest. Combining this technique with a proper ellipsoid shaping (e.g. augmenting the shape with the obstacle velocity, or the obstacle detection uncertainties) results in a robust obstacle avoidance behaviour. We validate our approach within extensive simulated experiments demonstrating (i) capability to satisfy all the constraints, and (ii) the avoidance reactivity even in challeging situations. We release with this paper the open source implementation. Copyright © 2019, The Authors. All rights reserved.

关键词： Obstacle detectors

Multi-Layer Disease Spread Model with a Water Distribution Network

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Multi-Layer Disease Spread Model with a Water Distribution N...

IEEE Conference on Decision and control

作者： Philip E. Paré Ji Liu Henrik Sandberg Karl H. Johansson Division of Decision and Control Systems KTH Royal Institute of Technology Sweden Department of Electrical and Computer Engineering Stony Brook University USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper proposes a layered networked SIWS (Susceptible-Infected-Water-Susceptible) model, for an SIS-type waterborne disease spreading over a human contact network connected to a water distribution network that has a pathogen spreading in it. Conditions for local and global stability of the healthy state, where no one is sick and the water network is not contaminated, are provided. We also pose an observability problem, and show under certain conditions if you observe some of the human contact network you can recover the pathogen levels in the water network.

关键词： Water pollution Pathogens Water resources Nickel Observability Sociology

Nonlinear observer with observability-based parameter adaptation for vehicle motion estimation

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IFAC-PapersOnLine 2018年第15期51卷 60-65页

作者： Marco, Vicent Rodrigo Kalkkuhl, Jens Seel, Thomas Control Systems Group Department of Electrical Engineering and Computer Science Technische Universität Berlin BerlinD-10587 Germany Research and Development Daimler AG Sindelfingen71059 Germany

In the framework of self-driving cars and driver-assistance systems the demand for reliable information about the vehicle ego-motion is increasing. This paper describes an estimation scheme, based on a nonlinear observer design, that provides velocity and attitude angle estimates. The approach relies on a state-affine representation of a kinematic model bolstered by a dynamic model-based measurement equation. By means of a thorough observability analysis, global exponential convergence is theoretically guaranteed. Additionally, in order to minimize the errors introduced by the dynamic model limitations, an observer tuning rule is proposed. The adaptation of the tuning parameters is built upon an online observability assessment of the system without the support of the dynamic model. Experimental results show that the presented approach reliably estimates the motion states. © 2018

关键词： Motion estimation Automobile drivers Automotive industry Dynamic models Kinematics Nonlinear analysis Nonlinear systems Observability Driver assistance system Estimation schemes Global exponential convergence Measurement equations Non linear observer Nonlinear observer design Observability analysis Parameter adaptation

Minimum Age-Energy Aware Cost in Wireless Powered Fog Computing Networks

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Minimum Age-Energy Aware Cost in Wireless Powered Fog Comput...

IEEE International Conference on Communications (ICC)

作者： Haina Zheng Ke Xiong Pingyi Fan Zhangdui Zhong Khaled Ben Letaief School of Computer and Information Technology Beijing Jiaotong University Beijing China Department of Electronic Engineering Tsinghua University Beijing China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China The Hong Kong University of Science and Technology Hong Kong

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

This paper investigates the optimal design of wireless powered fog computing networks, where a hybrid access point integrated with fog computing function (F-HAP) first charges an Internet of Things (IoT) device via wireless power transfer (WPT), and then the IoT device uses the harvested energy to compute real-time updates locally or offload the updates to the F-HAP for computing. For such a system, an age-energy aware cost function is defined to evaluate the system performance, based on which, an optimization problem is formulated to explore the minimum age-energy aware cost by jointly optimizing the time assignment, the transmit power, the computing frequency, as well as the computing mode selection, such that the given data processing task can be completed. Since the problem is non-convex with the discrete binary variable, variable substitution and Karush-Kuhn-Tucker (KKT) conditions are applied to solve it and some closed-form results on the optimal solution are derived. Numerical results show that the transmit power has much greater effects on the age-energy performance of the fog offloading mode than on that of the local computing mode. Moreover, when the IoT device is relatively close to the F-HAP, fog offloading is a better choice; Otherwise, local computing should be selected.

关键词： Edge computing Wireless communication Real-time systems Cost function Internet of Things System performance Time-frequency analysis

Glassy Behavior and Anomalous Transport in Chimney Ladder Crystals Induced by Soft Optical Phonons

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arXiv 2025年

作者： Mandyam, Srinivas V. Dong, Weicen Yan, Xiaoxian Zhao, Binru Lin, Junfa Xia, Tianlong Zhao, Zhiying Chen, Xi Ma, Jie Xing, Hui Grosche, F. Malte Baggioli, Matteo Department of Physics Harvard University CambridgeMA02135 United States Wilczek Quantum Center School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Key Laboratory of Artificial Structures and Quantum Control School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Shanghai Center for Complex Physics School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China School of Physics Beijing Key Laboratory of Opto-electronic Functional Materials & Micro-nano Devices Renmin University of China Beijing100872 China Renmin University of China Beijing100872 China Laboratory for Neutron Scattering Renmin University of China Beijing100872 China State Key Laboratory of Structural Chemistry Fujian Institute of Research The Structure of Matter Chinese Academy of Sciences Fujian Fuzhou350002 China Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Collaborative Innovation Center of Advanced Microstructures Jiangsu Nanjing210093 China Cavendish Laboratory University of Cambridge JJ Thomson Avenue CambridgeCB30HE United Kingdom

Nowotny chimney ladder (NCL) crystals present physical properties in between the contrasting paradigms of ideal crystal and amorphous solid, making them promising candidates for thermoelectric applications due to their inherently low thermal conductivity. Here, we report an extensive experimental characterization of the thermodynamic and thermoelectric transport properties of a large class of NCL materials, focusing on the intermetallic compound Ru2Sn3−δ. We show that the heat capacity of these NCL compounds exhibits a boson-peak-like glassy anomaly between 8 K and 14 K. By combining experimental measurements with density functional theory (DFT), we attribute its microscopic origin to extremely soft optical phonons that universally appear as a consequence of the chimney ladder sublattice structure. Additionally, the measured thermal conductivity and the thermoelectric response present distinct anomalous glass-like features that strongly correlate with the dynamics of the abundant soft optical phonons revealed by DFT. Our work demonstrates that soft modes in ordered crystals can induce glassy behavior, outlining a pathway to design metallic materials with low thermal conductivity and unique thermoelectric properties without the need for disorder or strong electronic correlations. © 2025, CC BY.

关键词： Glass

Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

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arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

Recognition of patient groups with sleep related disorders using bio-signal processing and deep learning

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arXiv 2021年

作者： Jarchi, Delaram Andreu-Perez, Javier Kiani, Mehrin Vysata, Oldrich Kuchynka, Jiri Prochazka, Ales Sanei, Saeid Smart Health Technologies Group School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Embedded and Intelligent Systems Laboratory School of Computer Science and Electronics University of Essex ColchesterCO4 3SQ United Kingdom Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague 6166 28 Czech Republic Department of Neurology Faculty of Medicine in Hradec Králové Charles University Hradec Králové500 05 Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6160 00 Czech Republic School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem. © 2021, CC BY-NC-ND.

关键词： Wavelet transforms

Resilient Estimation and control on k-Nearest Neighbor Platoons: A Network-Theoretic Approach

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Resilient Estimation and Control on k-Nearest Neighbor Plato...

作者： Pirani, Mohammad Hashemi, Ehsan Fidan, Baris Simpson-Porco, John W. Sandberg, Henrik Johansson, Karl Henrik Department of Automatic Control KTH Royal Institute of Technology China Department of Mechanical and Mechatronics Engineering University of Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Canada

This paper is concerned with the network-theoretic properties of so-called k-nearest neighbor intelligent vehicular platoons, where each vehicle communicates with k vehicles, both in front and behind. The network-theoretic properties analyzed in this paper play major roles in quantifying the resilience and robustness of three generic distributed estimation and control algorithms against communication failures and disturbances, namely resilient distributed estimation, resilient distributed consensus, and robust network formation. Based on the results for the connectivity measures of the k-nearest neighbor platoon, we show that extending the traditional platooning topologies (which were only based on interacting with nearest neighbors) to k-nearest neighbor platoons increases the resilience of distributed estimation and control algorithms to both communication failures and disturbances. © 2018

关键词： Motion compensation

When energy trading meets blockchain in electrical power system: The state of the art

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arXiv 2019年

作者： Wang, Naiyu Zhou, Xiao Lu, Xin Guan, Zhitao Wu, Longfei Du, Xiaojiang Guizani, Mohsen School of Control and Computer Engineering North China Electric Power University Beijing China Department of Mathematics and Computer Science Fayetteville State University FayettevilleNC United States Department of Computer and Information Science Temple University PhiladelphiaPA United States Electrical and Computer Engineering Department University of Idaho MoscowID United States

With the rapid growth of renewable energy resources, the energy trading began to shift from centralized to distributed manner. Blockchain, as a distributed public ledger technology, has been widely adopted to design new energy trading schemes. However, there are many challenging issues for blockchain‐based energy trading, i.e., low efficiency, high transaction cost, security & privacy issues. To tackle with the above challenges, many solutions have been proposed. In this survey, the blockchain‐based energy trading in electrical power system is thoroughly investigated. Firstly, the challenges in blockchain‐based energy trading are identified. Then, the existing energy trading schemes are studied and classified into three categories based on their main focus: energy transaction, consensus mechanism, and system optimization. And each category is presented in detail. Although existing schemes can meet the specific energy trading requirements, there are still many unsolved problems. Finally, the discussion and future directions are given. Copyright © 2019, The Authors. All rights reserved.

关键词： Blockchain