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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Yuan, Songyu Zhang, Jing Pan, Chen Zhang, Chunlong Wan, Minhong Zheng, Tao Gu, Jason Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

The field of Simultaneous Localization and Mapping(SLAM) has witnessed significant advancements in recent years. However, due to the difficulty of data obtains and ground-truth makes, there is a lack of real indoor scenarios datasets, especially the scenarios with less-texture, repeat-texture, extreme light condition, causing the slowly progress in indoor SLAM. In this paper, we present a dataset captured in a real indoor exhibition hall with diverse type of sensor data. Which contributes to diverse school of SLAM that using different sensors. We provide ground-truth 6DoF pose captured by motion capture devices, RGB-D data captured by a RealSense D455 camera. Laser-data captured by Ouster. And a high-resolution color point cloud captured by a laser scanner. This dataset offers three distinct sources of ground truth from real-world scenarios. It combines motion capture, ICP based laser localization, and visual localization methods to provide comprehensive and accurate reference data. This dataset is designed for evaluating positioning methods that employ various types of sensors, moving beyond a singular matrix-based evaluation approach. Besides, We show results of several state-of-the-art SLAM method in our datasets, illustrates the utility of our dataset and served as a reference for other researcher. We converge LiDAR-based SLAM with ground truth, made a good closure. An ensemble approach-based Visual SLAM, achieves results of odometry errors of 4% and loop closure position errors of 40 cm. Additionally, visual localization demonstrated an absolute position error of 21 cm using high-resolution point clouds. We highlight the potentials of our indoor datasets in LiDAR SLAM, RGB-D SLAM, and visual localization and combines method. The datasets are available at https://***/IMBAfarmer09/ExhibitionDataset © 2023 IEEE.

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Multiagent Consensus over Time-Invariant and Time-Varying Signed Digraphs via Eventual Positivity

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IEEE Transactions on Automatic Control 2023年第9期68卷 5429-5444页

作者： Fontan, Angela Wang, Lingfei Hong, Yiguang Shi, Guodong Altafini, Claudio Linköping University Division of Automatic Control Department of Electrical Engineering LinköpingSE-58183 Sweden KTH Royal Institute of Technology Division of Decision and Control Systems StockholmSE-10044 Sweden Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Tongji University Department of Control Science and Engineering Shanghai201804 China University of Sydney Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering SydneyNSW2008 Australia

Laplacian dynamics on signed digraphs have a richer behavior than those on nonnegative digraphs. In particular, for the so-called 'repelling' signed Laplacians, the marginal stability property (needed to achieve consensus) is not guaranteed a priori and, even when it holds, it does not automatically lead to consensus, as these signed Laplacians may lose rank even in strongly connected digraphs. Furthermore, in the time-varying case, instability can occur even when switching in a family of systems each of which corresponds to a marginally stable signed Laplacian with the correct corank. In this article, we present novel conditions for achieving consensus on signed digraphs based on the property of eventual positivity, a Perron-Frobenius (PF) type of property for signed matrices. The conditions we develop cover both time-invariant and time-varying cases. A particularly simple sufficient condition, valid in both cases, is that the Laplacians are normal matrices. Such condition can be relaxed in several ways. For instance, in the time-invariant case it is enough that the Laplacian has this PF property on the right side, but not on the left side (i.e., on the transpose). For the time-varying case, convergence to consensus can be guaranteed by the existence of a common Lyapunov function for all the signed Laplacians. All conditions can be easily extended to bipartite consensus. © 1963-2012 IEEE.

关键词： Lyapunov functions

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A Joint Tracking System: Robot is Online to Access Surveillance Views

A Joint Tracking System: Robot is Online to Access Surveilla...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Lin, Zheyuan Ji, Shanshan Wang, Wen Qin, Mengjie Yang, Rong Wan, Minhong Gu, Jason Li, Te Zhang, Chunlong Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

The application of robots in social life, equipped with sensors and actuators and embedded with AI, assists people in all aspects. However, the first perspective of the robot horizon is heavily constrained, which weakens its performance. A joint tracking system is designed and built to deal with this, by integrating a surveillance system with the robot visual, providing a third perspective. This system takes one horizontal view and two top views from various directions as inputs and matches a person among the frames and in time sequence. In order to deal with the identity match with a huge visual feature gap, a special dataset is collected, simultaneously labeling identities from a mobile robot perspective and multiple indoor static surveillance monitors. The experiment shows that such match is a task worth exploring that can be better handled by training on our dataset than existing open source Re-identification (Re-id) datasets. Moreover, in the real scenario, this system improves the performance on issues like in and out of the robot's field of vision and heavy occlusion by people or objects. © 2023 IEEE.

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Net Load Forecasting with Disaggregated Behind-the-Meter PV Generation

Net Load Forecasting with Disaggregated Behind-the-Meter PV ...

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2022 IEEE Industry Applications Society Annual Meeting, IAS 2022

作者： Stratman, Anne Hong, Tianqi Yi, Ming Zhao, Dongbo University of Nebraska-Lincoln Department of Electrical and Computer Engineering LincolnNE United States Argonne National Lab Energy Systems Division LemontIL United States Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering TroyNY United States

ISBN: (数字)9781665478151

ISBN: (纸本)9781665478151

With increasing adoption of residential PV systems, net load forecasting is gradually shifting from forecasting pure load to forecasting pure load with PV generation. This paper explicitly compares two methods of net load forecasting for systems with high behind-the-meter (BTM) PV penetration. The first method is an additive method, in which PV generation and pure load are forecasted separately and combined to produce a net load forecast. First, a disaggregation algorithm is applied to aggregate net load measurements of residential homes to separate the pure load and PV generation. Then, a long short-term memory (LSTM) model is used to forecast pure load and PV separately using the historical disaggregated pure load and PV, respectively, and weather factors. The results are combined to generate a net load forecast. The additive model is compared to a direct net load forecast from an LSTM model. Results show that over the five-month test horizon, the additive method decreases the root mean square error (RMSE), maximum absolute error, and mean absolute error (MAE) of the net load forecast by 6.13%, 3.63%, and 6.06% respectively, compared to the direct method. © 2022 IEEE.

关键词： Errors

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In-situ fabrication of on-chip 1T'-MoTe_(2)/Ge Schottky junction photodetector for self-powered broadband infrared imaging and position sensing

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Nano Research 2024年第6期17卷 5587-5594页

作者： Menglei Zhu Kunxuan Liu Di Wu Yunrui Jiang Xue Li Pei Lin Zhifeng Shi Xinjian Li Ran Ding Yalun Tang Xuechao Yu Longhui Zeng School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin UniversityChangchun 130012China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

High-sensitivity room-temperature multi-dimensional infrared(IR)detection is crucial for military and civilian ***,the gapless electronic structures and unique optoelectrical properties have made the two-dimensional(2D)topological semimetals promising candidates for the realization of multifunctional optoelectronic ***,we demonstrated the in-situ construction of high-performance 1T’-MoTe_(2)/Ge Schottky junction device by inserting an ultrathin AlOx passivation *** good detection performance with an ultra-broadband detection wavelength range of up to 10.6 micron,an ultrafast response time of~160 ns,and a large specific detectivity of over 109 Jones in mid-infrared(MIR)range surpasses that of most 2D materials-based IR sensors,approaching the performance of commercial IR *** on-chip integrated device arrays with 64 functional detectors feature high-resolution imaging capability at room *** these outstanding detection features have enabled the demonstration of position-sensitive detection *** demonstrates an exceptional position sensitivity of 14.9 mV/mm,an outstanding nonlinearity of 6.44%,and commendable trajectory tracking and optoelectronic demodulation *** study not only offers a promising route towards room-temperature MIR optoelectronic applications,but also demonstrates a great potential for application in optical sensing systems.

关键词： MoTe_(2) broadband photodetection Schottky junction imaging position sensitive detector

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CKTGNN: CIRCUIT GRAPH NEURAL NETWORK FOR ELECTRONIC DESIGN AUTOMATION 11

CKTGNN: CIRCUIT GRAPH NEURAL NETWORK FOR ELECTRONIC DESIGN A...

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11th International Conference on Learning Representations, ICLR 2023

作者： Dong, Zehao Cao, Weidong Zhang, Muhan Tao, Dacheng Chen, Yixin Zhang, Xuan Department of Computer Science & Engineering Washington University St.Louis United States Department of Electrical & Systems Engineering Washington University St.Louis United States Institute for Artificial Intelligence Peking University China School of Computer Science The University of Sydney Australia

The electronic design automation of analog circuits has been a longstanding challenge in the integrated circuit field due to the huge design space and complex design trade-offs among circuit *** the past decades, intensive research efforts have mostly been paid to automate the transistor sizing with a given circuit *** recognizing the graph nature of circuits, this paper presents a Circuit Graph Neural Network (CktGNN) that simultaneously automates the circuit topology generation and device sizing based on the encoder-dependent optimization ***, CktGNN encodes circuit graphs using a two-level GNN framework (of nested GNN) where circuits are represented as combinations of subgraphs in a known subgraph *** this way, it significantly improves design efficiency by reducing the number of subgraphs to perform message ***, another critical roadblock to advancing learning-assisted circuit design automation is a lack of public benchmarks to perform canonical assessment and reproducible *** tackle the challenge, we introduce Open Circuit Benchmark (OCB), an open-sourced dataset that contains 10K distinct operational amplifiers with carefully-extracted circuit *** is also equipped with communicative circuit generation and evaluation capabilities such that it can help to generalize CktGNN to design various analog circuits by producing corresponding *** on OCB show the extraordinary advantages of CktGNN through representation-based optimization frameworks over other recent powerful GNN baselines and human experts' manual *** work paves the way toward a learning-based open-sourced design automation for analog *** source code is available at https://***/zehao-dong/CktGNN. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Timing circuits

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Multimedia Fingerprinting Codes Resistant to Linear Attacks and Adversarial Noise

Multimedia Fingerprinting Codes Resistant to Linear Attacks ...

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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Fernandez, Marcel Kabatiansky, Grigory Kamel, Ibrahim Miao, Ying Rabie, Tamer Farouk The Technical University of Catalonia Department of Network Engineering Spain Center for Next Generation Wireless and IoT Skolkovo Institute of Science and Technology Russia University of Sharjah Electrical and Computer Engineering United Arab Emirates Institute of Engineering Information and Systems University of Tsukuba Japan

ISBN: (纸本)9798350335590

It has recently been shown that there are no multimedia fingerprinting codes that can find all malicious users when they use arbitrary linear attacks plus adversarial noise. It is shown that such codes exist if the complete recovery property is limited to the IPP property, i.e., the property to find at least one malicious user. Moreover, we extend this property to a property that allows us to detect all users whose contribution to the forgery is large enough. Efficient decoding (tracing traitors) algorithms are developed for these codes. © 2023 IEEE.

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An Automatic Extraction of Features from Water Bodies by using Contrast Vision Transformer 2

An Automatic Extraction of Features from Water Bodies by usi...

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2nd IEEE International Conference on Integrated Intelligence and Communication systems, ICIICS 2024

作者： Madhumitha, A. Al-Fatlawi, Muhammed Sai Srinivas, T. Aditya Ramachandra, A.C. Venkatasubramanian, R. Department of Computer Science and Business Systems Bannari Amman Institute of Technology Sathyamangalam Erode India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Artificial Intelligence and Machine Learning Jayaprakash Naryan College of Engineering Mahabubnagar India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Electrical and Electronics Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai India

ISBN: (纸本)9798331504960

In recent days, for strengthening the climate change adaption water features are utilizing as the most crucial environmental element. The integration of Remote Sensing (RS) with Artificial Intelligence (AI) is becoming the major sought-after approach for extracting the features of water information. In existing, the Faster Regional Convolution Neural Network (FR_CNN) is utilized for the water bodies’ extraction. However, the existing FR_CNN model struggled with computational complexity. To overcome this issue, Contrast Vision Transformer (CoVT) is proposed to extract features from water bodies. The transformer with self-attention mechanism reduces the computational complexity by eliminating regional proposal networks. Initially, the satellite images are taken from sentinel-2 dataset and further processed into preprocessing. In preprocessing Gaussian Median Filter (GMF) and Atmospheric Correction (AC) are utilized to reduce the noise and atmospheric effects from images. After that, proposed CoVT extract features from preprocessed images and fed into projection head to generate projected features. Finally, the projected features are further processed with prediction head to predict the satellite image features of water bodies. From the results, the proposed CoVT provided better results when compared to existing FR_CNN by providing results such as accuracy (99.4%), precision (99.1%), recall (98.5%) and F1-score (98.7%) respectively. © 2024 IEEE.

关键词： Median filters

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Benchmarking Convolutional Neural Network Inference on Low-Power Edge Devices

Benchmarking Convolutional Neural Network Inference on Low-P...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Oscar Ferraz Helder Araujo Vitor Silva Gabriel Falcao Instituto de Telecomunicações Dept. of Electrical and Computer Engineering University of Coimbra Portugal Institute of Systems and Robotics

The massive adoption of IoT devices, the recent developments in the efficiency of AI systems, and the increase of edge computational power, accelerated the deployment of edge AI systems. The implementation of these systems through the use of low-power embedded devices scattered across the edges of a network allows for reduced latency and cost, compared to traditional cloud-based AI computing systems. As a result of the low-complexity AI models and the available low-power embedded systems on the market, this paper provides a comparative study on the inference performance of convolutional neural networks for different edge devices, by exploiting low-power GPUs and dedicated AI hardware. The benchmark results were able to achieve 864 inferences/s for the Jetson AGX Xavier board on a pre-trained SqueezeNet, while reaching a high power efficiency of 52.6 inferences/s per Watt. For the dedicated Movidius neural stick, the system requires only 1.5 W for processing 24.2 inferences/s.

关键词： Performance evaluation Benchmark testing Signal processing Throughput Hardware Convolutional neural networks Internet of Things

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A Comprehensive Methodology for Assessing the Economic Viability of EV Charging Infrastructure in Brazil

A Comprehensive Methodology for Assessing the Economic Viabi...

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Smart Power & Internet Energy systems (SPIES), International Conference on

作者： Daywes Pinheiro Neto António Paulo Coimbra Aníbal T. De Almeida Tony R. Almeida Pedro Moura Letícia C. Ucker Raphael A. Gomes Alana S. Magalhães Center for Experimental and Technological Research and Studies Federal Institute of Goiás Brazil Dpt. of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

This study proposes a comprehensive methodology to assess the economic viability of electric vehicle (EV) charging infrastructure projects in Brazil, specifically targeting connections with a capacity of up to 112.5 kW, which are subject to flat electricity tariffs. The methodology employs a novel EV energy consumption model, integrates the regulatory framework of net metering and relevant tax considerations, explores the potential cost-saving benefits of photovoltaic (PV) system integration, and utilizes key economic indicators like Net Present Value and Discounted Payback Time to quantify project profitability. By accounting for a set of EV demand scenarios (low, moderate, and high), the methodology provides a multifaceted assessment of project viability. A case study demonstrates the methodology's application, highlighting the potential economic benefits of such investments. The results suggest that the minimum charging service fee required for economic viability ranges from 0.17 to 0.29 USD/kWh, with a clear cost advantage associated with PV integration observed across all scenarios.

关键词： Economics Photovoltaic systems Costs Finance Transportation Tariffs System integration Charging stations Electric vehicle charging Sustainable development

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