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Concurrent Flow-Based Localization and Mapping in Time-Invariant Flow Fields*

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arXiv 2019年

作者： Song, Zhuoyuan Mohseni, Kamran Department of Mechanical and Aerospace Engineering University of Florida Department of Mechanical Engineering University of Hawai‘i at Mānoa HonoluluHI96822 United States Department of Mechanical and Aerospace Engineering Department of Electrical and Computer Engineering Institute for Networked Autonomous Systems University of Florida GainesvilleFL32611 United States

We present the concept of concurrent flow-based localization and mapping (FLAM) for autonomous field robots navigating within background flows. Different from the classical simultaneous localization and mapping (SLAM) problem, where the robot interacts with discrete features, FLAM utilizes the continuous flow fields as navigation references for mobile robots and provides flow field mapping capability with in-situ flow velocity observations. This approach is of importance to underwater vehicles in mid-depth oceans or aerial vehicles in GPS-denied atmospheric circulations. This article introduces the formulation of FLAM as a full SLAM solution motivated by the feature-based GraphSLAM framework. The performance of FLAM was demonstrated through simulation within artificial flow fields that represent typical geophysical circulation phenomena: a steady single-gyre flow field and a double-gyre flow field with unsteady turbulent perturbations. The results indicate that FLAM provides significant improvements in the robots’ localization accuracy and a consistent approximation of the background flow field. It is also shown that FLAM leads to smooth robot trajectory estimates. Copyright © 2019, The Authors. All rights reserved.

关键词： Flow fields

Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix

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arXiv 2020年

作者： Xu, Kaijie Pedrycz, Witold Li, Zhiwu Xing, Mengdao School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of remote sensing science and technology School of Electronic Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau999078 China National Laboratory of Radar Signal Processing Xidian University Xi’an710071 China Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi’an710071 China National Key Laboratory of Microwave Imaging Technology Institute of Electronics Chinese Academy of Sciences Beijing100190 China

As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of GrC. By generating centroids (prototypes) and partition matrix, fuzzy clustering is a commonly encountered way of information granulation. As a reverse process of granulation, degranulation involves data reconstruction completed on a basis of the granular representatives (decoding information granules into numeric data). Previous studies have shown that there is a relationship between the reconstruction error and the performance of the granulation process. Typically, the lower the degranulation error is, the better performance of granulation process becomes. However, the existing methods of degranulation usually cannot restore the original numeric data, which is one of the important reasons behind the occurrence of the reconstruction error. To enhance the quality of reconstruction (degranulation), in this study, we develop an augmented scheme through modifying the partition matrix. By proposing the augmented scheme, we dwell on a novel collection of granulation-degranulation mechanisms. In the constructed approach, the prototypes can be expressed as the product of the dataset matrix and the partition matrix. Then, in the degranulation process, the reconstructed numeric data can be decomposed into the product of the partition matrix and the matrix of prototypes. Both the granulation and degranulation are regarded as generalized rotation between the data subspace and the prototype subspace with the partition matrix and the fuzzification factor. By modifying the partition matrix, the new partition matrix is constructed through a series of matrix operations. We offer a thorough analysis of the developed scheme. Copyright © 2020, The Authors. Al

关键词： Granulation

Quantized frank-wolfe: Faster optimization, lower communication, and projection free

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arXiv 2019年

作者： Zhang, Mingrui Chen, Lin Mokhtari, Aryan Hassani, Hamed Karbasi, Amin Department of Statistics and Data Science Yale University New HavenCT06511 United States Yale Institute for Network Science Department of Electrical Engineering Yale University New HavenCT06511 United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical Engineering and Computer Science Yale University New HavenCT06511 United States

How can we efficiently mitigate the overhead of gradient communications in distributed optimization? This problem is at the heart of training scalable machine learning models and has been mainly studied in the unconstrained setting. In this paper, we propose Quantized Frank-Wolfe (QFW), the first projection-free and communication-efficient algorithm for solving constrained optimization problems at scale. We consider both convex and non-convex objective functions, expressed as a finite-sum or more generally a stochastic optimization problem, and provide strong theoretical guarantees on the convergence rate of QFW. This is accomplished by proposing novel quantization schemes that efficiently compress gradients while controlling the noise variance introduced during this process. Finally, we empirically validate the efficiency of QFW in terms of communication and the quality of returned solution against natural baselines. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Multi modal semantic segmentation using synthetic data

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arXiv 2019年

作者： Srivastava, Kartik Singh, Akash Kumar Hegde, Guruprasad M. Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani. Hyderabad India Department of Electrical Engineering Indian Institute of Technology Kanpur. Kanpur India Robert Bosch Research and Technology Center Bangalore India

Semantic understanding of scenes in threedimensional space (3D) is a quintessential part of robotics oriented applications such as autonomous driving as it provides geometric cues such as size, orientation and true distance of separation to objects which are crucial for taking mission critical decisions. As a first step, in this work we investigate the possibility of semantically classifying different parts of a given scene in 3D by learning the underlying geometric context in addition to the texture cues BUT in the absence of labelled real-world datasets. To this end we generate a large number of synthetic scenes, their pixel-wise labels and corresponding 3D representations using CARLA software framework. We then build a deep neural network that learns underlying category specific 3D representation and texture cues from color information of the rendered synthetic scenes. Further on we apply the learned model on different real world datasets to evaluate its performance. Our preliminary investigation of results show that the neural network is able to learn the geometric context from synthetic scenes and effectively apply this knowledge to classify each point of a 3D representation of a scene in real-world. Copyright © 2019, The Authors. All rights reserved.

关键词： Autonomous vehicles

Underwater acoustic intensity field reconstruction by kriged compressive sensing 13

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Underwater acoustic intensity field reconstruction by kriged...

13th ACM International Conference on Underwater Networks and systems, WUWNet 2018

作者： Sun, Jie Yu, Jiancheng Zhang, Aiqun Song, Aijun Zhang, Fumin State Key Laboratory of Robotics Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Electrical Engineering University of Alabama TuscaloosaAL35487 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (纸本)9781450361934

This paper presents a novel Kriged Compressive Sensing (KCS) approach for the reconstruction of underwater acoustic intensity fields sampled by multiple gliders following sawtooth sampling patterns. Blank areas in between the sampling trajectories may cause unsatisfying reconstruction results. The KCS method leverages spatial statistical correlation properties of the acoustic intensity field being sampled to improve the compressive reconstruction process. Virtual data samples generated from a kriging method are inserted into the blank areas. We show that by using the virtual samples along with real samples, the acoustic intensity field can be reconstructed with higher accuracy when coherent spatial patterns exist. Corresponding algorithms are developed for both unweighted and weighted KCS methods. By distinguishing the virtual samples from real samples through weighting, the reconstruction results can be further improved. Simulation results show that both algorithms can improve the reconstruction results according to the PSNR and SSIM metrics. The methods are applied to process the ocean ambient noise data collected by the Sea-Wing acoustic gliders in the South China Sea. © 2018 Association for Computing Machinery.

关键词： Kriging

Electromagnetic time reversal applied to fault location: On the properties of back-injected signals 20

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Electromagnetic time reversal applied to fault location: On ...

20th Power systems Computation Conference, PSCC 2018

作者： Wang, Zhaoyang Razzaghi, Reza Paolone, Mario Rachidi, Farhad Laboratory Swiss Federal Institute of Technology EPFL Lausanne Switzerland Swiss Federal Institute of Technology EPFL Lausanne Switzerland Department of Electrical and Computer Systems Engineering Monash University Melbourne Australia

ISBN: (纸本)9781910963104

By using the electromagnetic time reversal (EMTR) theory, the paper studies its properties in order to derive a new fault location method to be used in power networks. It is shown that, in the reversed-time stage, the current signal observed at the true fault location can be clearly distinguished since it appears as a time-delayed copy of the back-injected fault-originated transient signal. Then, based on this similarity property, a fault location method is derived. Finally, the method is numerically validated with reference to a reproducible simulated power network composed of an inhomogeneous multi-conductor transmission-line system. © 2018 Power systems Computation Conference.

关键词： Location

Efficient creation of datasets for data-driven power system applications

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arXiv 2019年

作者： Venzke, Andreas Molzahn, Daniel K. Chatzivasileiadis, Spyros Department of Electrical Engineering Technical University of Denmark 2800 Kgs Lyngby Denmark School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30313 United States Energy Systems Division Argonne National Laboratory LemontIL60439 United States

Advances in data-driven methods have sparked renewed interest for applications in power systems. Creating datasets for successful application of these methods has proven to be very challenging, especially when considering power system security. This paper proposes a computationally efficient method to create datasets of secure and insecure operating points. We propose an infeasibility certificate based on separating hyperplanes that can a-priori characterize large parts of the input space as insecure, thus significantly reducing both computation time and problem size. Our method can handle an order of magnitude more control variables and creates balanced datasets of secure and insecure operating points, which is essential for data-driven applications. While we focus on N-1 security and uncertainty, our method can extend to dynamic security. For PGLib-OPF networks up to 500 buses and up to 125 control variables, we demonstrate drastic reductions in unclassified input space volumes and computation time, create balanced datasets, and evaluate an illustrative data-driven application. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Constructions of Partial MDS Codes over Small Fields

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Constructions of Partial MDS Codes over Small Fields

作者： Gabrys, Ryan Yaakobi, Eitan Blaum, Mario Siegel, Paul H. Spawar Systems Center San Diego San DiegoCA92115 United States Department of Computer Science Technion - Israel Institute of Technology Haifa32000 Israel IBM Research Division Almaden Research Center San JoseCA95120 United States Department of Electrical and Computer Engineering University of California at San Diego San DiegoCA92093 United States Center for Memory and Recording Research University of California at San Diego San DiegoCA92093 United States

Partial MDS (PMDS) codes are a class of erasure-correcting array codes that combine local correction of the rows with global correction of the array. An m× n array code is called an (rs) PMDS code if each row belongs to an [n, n-r, r+1] MDS code and the code can correct erasure patterns consisting of r erasures in each row together with s more erasures anywhere in the array. While a recent construction by Calis and Koyluoglu generates (r;s) PMDS codes for all r and s, its field size is exponentially large. In this paper, a family of PMDS codes with field size O\left (max m, nr+ss}\right) is presented for the case where r= O(1), s= O(1). © 1963-2012 IEEE.

关键词： Codes (symbols)

Impact of intra-grain spin wave reflections on nano-contact spin torque oscillators

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arXiv 2020年

作者： Eklund, Anders J. Dvornik, Mykola Qejvanaj, Fatjon Jiang, Sheng Chung, Sunjae Åkerman, Johan Gunnar Malm, B. Department of Physics University of Oslo Box 1048 Blindern Oslo0316 Norway Department of Physics University of Gothenburg Gothenburg412 96 Sweden NanOsc AB Electrum 205 Kista164 40 Sweden Department of Applied Physics School of Engineering Sciences KTH Royal Institute of Technology Electrum 229 Kista164 40 Sweden Department of Physics Education Korea National University of Education Cheongju28173 Korea Republic of Division of Electronics and Embedded Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Electrum 229 Kista164 40 Sweden

We investigate the origin of the experimentally observed varying current-frequency nonlinearity of the propagating spin wave mode in nano-contact spin torque oscillators. Nominally identical devices with 100 nm diameter are characterized by electrical microwave measurements and show large variation in the generated frequency as a function of drive current. This quantitative and qualitative device-to-device variation is described in terms of continuous and discontinuous nonlinear transitions between linear current intervals. The thin film grain microstructure in our samples is determined using atomic force and scanning electron microscopy to be on the scale of 30 nm. Micromagnetic simulations show that the reflection of spin waves against the grain boundaries results in standing wave resonance configurations. For a simulated device with a single artificial grain, the frequency increases linearly with the drive current until the decreased wavelength eventually forces another spin wave anti-node to be formed. This transition results in a discontinuous step in the frequency versus current relation. Simulations of complete, randomly generated grain microstructures additionally shows continuous nonlinearity and a resulting device-to-device variation in frequency that is similar to the experimental levels. The impact of temperature from 4 K to 300 K on the resonance mode-transition nonlinearity and frequency noise is investigated using simulations and it is found that the peak levels of the spectral linewidth as a function of drive current agrees quantitatively with typical levels found in experiments at room temperature. Copyright © 2020, The Authors. All rights reserved.

关键词： Scanning electron microscopy