检索结果-内蒙古大学图书馆

IEEE Transactions on Green Communications and Networking 2024年第2期9卷 1-1页

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Key Lab of Industrial Computer Control Engineering of Hebei Province China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China

This paper deals with a cooperation communication problem (relay selection and power control) for mobile underwater acoustic communication networks. To achieve satisfactory transmission capacity, we propose a reinforcement-learning-based cooperation communication scheme to efficiently resist the highly dynamic communication links and strongly unknown time-varying channel states caused by the mobility of Autonomous Underwater Vehicles (AUVs). Firstly, a particular Markov decision process is developed to model the dynamic relay selection process of mobile AUV in the unknown scenario. In the developed model, an experimental statistical-based partition mechanism is proposed to cope with the greatly increasing dimension of the state space caused by the mobility of AUV, reducing the search optimization difficulty. Secondly, a dual-thread reinforcement learning structure with actual and virtual learning threads is proposed to efficiently track the superior relay action. In the actual learning thread, the proposed improved probability greedy policy enables the AUV to strengthen the exploration for the reward information of potential superior relays on the current state. Meanwhile, in the virtual learning thread, the proposed upper-confidence-bound-index-based uncertainty estimation method can estimate the action-reward level of historical states. Consequently, the combination of actual and virtual learning threads can efficiently obtain satisfactory Q value information, thereby making superior relay decision-making in a short time. Thirdly, a power control mechanism is proposed to reuse the current observed action-reward information and transform the multiple unknown parameter nonlinear joint power optimization problem into a convex optimization problem, thereby enhancing network transmission capacity. Finally, simulation results verify the effectiveness of the proposed scheme. IEEE

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Long-Range Vehicle Detection of LiDAR using Adaboost Classification

Long-Range Vehicle Detection of LiDAR using Adaboost Classif...

引用

2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Lim, Na-Young Lee, Jeon-Hyeok Park, Tae-Hyoung Chungbuk National University Department of Intelligent Systems & Robotics Cheongju Korea Republic of Chungbuk National University Department of Control & Robot Engineering Cheongju Korea Republic of

ISBN: (纸本)9798331531614

In recent developments, autonomous racing has garnered attention as it aims to overcome the limitations of standard autonomous driving systems. Achieving safe racing conditions necessitates both fast and long-range perception. However, current 3D LiDAR object detection methods face challenges with high computational costs and limited detection ranges. These issues make them unsuitable for racing scenarios. To address these challenges, this paper proposes a clustering-based long-range vehicle detection method that relies solely on LiDAR. First, the method removes ground points and foreground points and clusters the remaining points. Subsequently, these clusters are classified as vehicles using AdaBoost, generating 2D bounding boxes in the range view. Experimental results demonstrate superior performance, achieving a computational efficiency of 53 Hz and a long-range detection accuracy of over 80%, compared to voxel-based and range-based methods. This approach offers a viable solution for autonomous racing environments. © 2025 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

High-definition event frame generation using SoC FPGA devices 26

High-definition event frame generation using SoC FPGA device...

引用

26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Blachut, Krzysztof Kryjak, Tomasz AGH University of Krakow Embedded Vision Systems Group Department of Automatic Control and Robotics Krakow Poland

ISBN: (纸本)9798350304985

In this paper we have addressed the implementation of the accumulation and projection of high-resolution event data stream (HD - 1280×720 pixels) onto the image plane in FPGA devices. The results confirm the feasibility of this approach, but there are a number of challenges, limitations and trade-offs to be considered. The required hardware resources of selected data representations, such as binary frame, event frame, exponentially decaying time surface and event frequency, were compared with those available on several popular platforms from AMD Xilinx. The resulting event frames can be used for typical vision algorithms, such as object classification and detection, using both classical and deep neural network methods. © 2023 Division of Signal Processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

Social NSTransformers: Low-Quality Pedestrian Trajectory Prediction

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5575-5588页

作者： Jiang, Zihan Ma, Yiqun Shi, Bingyu Lu, Xin Xing, Jian Goncalves, Nuno Jin, Bo Suzhou215000 China Northeast Forestry University College of Computer and Control Engineering Harbin150000 China University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Coimbra3030-290 Portugal

This article introduces a novel model for low-quality pedestrian trajectory prediction, the social nonstationary transformers (NSTransformers), that merges the strengths of NSTransformers and spatiotemporal graph transformer (STAR). The model can capture social interaction cues among pedestrians and integrate features across spatial and temporal dimensions to enhance the precision and resilience of trajectory predictions. We also propose an enhanced loss function that combines diversity loss with logarithmic root mean squared error (log-RMSE) to guarantee the reasonableness and diversity of the generated trajectories. This design adapts well to complex pedestrian interaction scenarios, thereby improving the reliability and accuracy of trajectory prediction. Furthermore, we integrate a generative adversarial network (GAN) to model the randomness inherent in pedestrian trajectories. Compared to the conventional standard Gaussian distribution, our GAN approach better simulates the intricate distribution found in pedestrian trajectories, enhancing the trajectory prediction's diversity and robustness. Experimental results reveal that our model outperforms several state-of-the-art methods. This research opens the avenue for future exploration in low-quality pedestrian trajectory prediction. © 2024 IEEE.

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

Navigating the Future: Advancing Autonomous Vehicles through Robust Target Recognition and Real-Time Avoidance 4

Navigating the Future: Advancing Autonomous Vehicles through...

引用

4th International Conference on control Theory and Applications, ICoCTA 2024

作者： Hussein, Mohammed A. M. Habib, Maki K. The American University in Cairo Robotics Control and Smart Systems Cairo Egypt The American University in Cairo Department of Mechanical Engineering Cairo Egypt

ISBN: (纸本)9798331506155

This research addresses the critical challenge of enhancing object recognition and real-Time response capabilities in autonomous vehicles (AVs) under varying simulated conditions, which is crucial for ensuring both navigational safety and operational efficiency. Utilizing the Carla 0.9.14 simulator and Unreal Engine 4.26 on Ubuntu 20.04, we focus on improving the detection and classification of key on-road obstacles-vehicles, pedestrians, and cyclists-using the YOLOv7 object detection algorithm. By integrating advanced sensory technologies, specifically stereo vision cameras and LIDAR, we create a dynamic testing environment that simulates diverse urban and rural scenarios. Our methodology enhances the YOLOv7 algorithm's accuracy and speed through extensive training on a meticulously curated dataset of 4,113 images, reflecting a broad spectrum of environmental conditions, including varying lighting and weather conditions. This rigorous approach yielded a significant increase in mean average precision (mAP) from 64.3% to 76.3%, and enhanced the algorithm's reliability, with notable improvements over previous models. The research delineates a clear advancement in AV technology by demonstrating substantial improvements in object detection metrics, contributing foundational insights for future implementations in real-world settings and supporting the further development of real-Time avoidance systems. This study not only progresses the field of AV but also sets a new benchmark for object detection performance, aligning with industry and academic goals to optimize AV systems for complex and unpredictable driving scenarios. © 2024 IEEE.

关键词： Stereo image processing

来源：评论

学校读者我要写书评

暂无评论

Adaptive observer for a LTV system with partially unknown state matrix and delayed measurements 14

Adaptive observer for a LTV system with partially unknown st...

引用

14th International Congress on Ultra Modern Telecommunications and control systems and Workshops, ICUMT 2022

作者： Bobtsov, Alexey Nikolaev, Nikolay Slita, Olga Kozachek, Olga Oskina, Olga Itmo University Institute of Problems of Mechanical Engineering Laboratory 'Control of Complex Systems' Department of Control Systems and Robotics Saint-Petersburg Russia Itmo University Department of Control Systems and Robotics Saint-Petersburg Russia

ISBN: (数字)9798350398663

ISBN: (纸本)9798350398663

Problem of adaptive state observer synthesis for linear time-varying (LTV) system with unknown time-varying parameter and delayed output measurements is considered. State observation problem has attracted the attention of many researchers [1]. In this paper the results proposed in the [2]-[4] are developed. It is supposed that the state matrix can be represented as sum of known and unknown parts. Output vector is measured with known constant delay. An adaptive identification algorithm which reconstructs unknown state and unknown time-varying parameter is proposed. © 2022 IEEE.

关键词： Time varying control systems

来源：评论

学校读者我要写书评

暂无评论

LiFT: Lightweight, FPGA-Tailored 3D Object Detection Based on LiDAR Data 18th

LiFT: Lightweight, FPGA-Tailored 3D Object Detection Based o...

引用

18th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2025

作者： Lis, Konrad Kryjak, Tomasz Gorgoń, Marek Embedded Vision Systems Group Department of Automatic Control and Robotics AGH University of Krakow Al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031878961

This paper presents LiFT, a lightweight, fully quantized 3D object detection algorithm for LiDAR data, optimized for real-time inference on FPGA platforms. Through an in-depth analysis of FPGA-specific limitations, we identify a set of FPGA-induced constraints that shape the algorithm’s design. These include a computational complexity limit of 30 GMACs (billion multiply-accumulate operations), INT8 quantization for weights and activations, 2D cell-based processing instead of 3D voxels, and minimal use of skip connections. To meet these constraints while maximizing performance, LiFT combines novel mechanisms with state-of-the-art techniques such as reparameterizable convolutions and fully sparse architecture. Key innovations include the Dual-bound Pillar Feature Net, which boosts performance without increasing complexity, and an efficient scheme for INT8 quantization of input features. With a computational cost of just 20.73 GMACs, LiFT stands out as one of the few algorithms targeting minimal-complexity 3D object detection. Among comparable methods, LiFT ranks first, achieving an mAP of 51.84% and an NDS of 61.01% on the challenging NuScenes validation dataset. The code will be available at https://***/vision-agh/lift. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 3d object detection FPGA LiDAR NuScenes quantisation

来源：评论

学校读者我要写书评

暂无评论

Combined Filters Design, Using the Principle of Internal Models

Combined Filters Design, Using the Principle of Internal Mod...

引用

2024 International Russian Automation Conference, RusAutoCon 2024

作者： Gaiduk, Anatoly Denisenko, Darya Prokopenko, Nikolay Southern Federal University Scientific Design Office Robotics and Control Systems Department of Automatic Control Systems Rostov-on-Don Taganrog Russia Department of scientific research Don State Technical University Rostov-on-Don Russia Department of Automatic Control Systems Southern Federal University Rostov-on-Don Russia Don State Technical University Department of Information Systems and Radio Engineering Rostov-on-Don Russia

To design active analog, discrete-analog and digital filters a new method is suggested, taking into account the conditions of selective invariance and using the internal models principle of the dynamic systems. For this purpose, the structure of each basic filter ensures the presence of an explicit spectral model of the filtered signal. Such a filter is selectively invariant, and this property depend only on the spectrum-setting parameters and do not depend on other parameters. It is suggest-ed to carry out the design of the combined selective filters by integration of the suggested basic second-order filters, focusing on the log magnitude plot of the latter. This makes possible to minimize the order of the combined both analog and digital filters. The combined selective filters are distinguished by high stability of selective properties and can be used in the systems for measurement, signal processing, data transmission, as well as automatic and automated control of various social, production and special facilities. © 2024 IEEE.

关键词： Wiener filtering

来源：评论

学校读者我要写书评

暂无评论

Signal Processing for Acoustic Emission Signature Analysis and Defect Detection 26

Signal Processing for Acoustic Emission Signature Analysis a...

引用

26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Altay, Yeldos A. Kuzivanov, Dmitry O. Altay, Dinara A. Fedorov, Alexey V. Satbayev University Department of Robotics and Technical Means of Automation Almaty Kazakhstan ITMO University Faculty of Control Systems and Robotics Saint-Petersburg Russia Military Engineering Institute of Radio Electronics and Communications Department of Natural Sciences Almaty Kazakhstan

ISBN: (纸本)9798350361728

This article presents the results of implementing a digital signal processing method for analyzing the acoustic emission (AE) signature and detecting defects such as cracks and pores. The signal processing method is based on a cascade connection of digital high-pass filters and ensures the selection of informative signals and increases the signal-to-interference ratio. In order to control the formation of defects in the process of selective laser melting, the paper presents the results of experimental testing of the cascade filtration method for detecting defects in the internal structure such as cracks and pores. The signal components recorded during the development of defects during the growth of additive manufacturing products were extracted. AE signatures were analyzed and statistical relationships were assessed. The relationship between the parameters of the AE signal and the values of laser radiation power has been identified, which characterizes the process of defect formation. © 2024 IEEE.

关键词： High pass filters

来源：评论

学校读者我要写书评

暂无评论

Supervisory control for Smart Manufacturing Using FIWARE 3

Supervisory Control for Smart Manufacturing Using FIWARE

引用

3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Menexis, Antonios N. Fragkoulis, Dimitrios G. Koumboulis, Fotis N. Kouvakas, Nikolaos D. School of Science National and Kapodistrian University of Athens Robotics Automatic Control and Cyber-Physical Systems Laboratory Department of Digital Industry Technologies Euboea 34400 Greece

ISBN: (纸本)9798331540319

The problem of providing smart manufacturing units, via supervisor control implemented in FIWARE, is studied. In order to investigate the problem at hand, an indicative manufacturing unit is considered, and the desired safe performance of the unit is achieved via a supervisory control architecture, being implemented in cloud computing environment. The model of the manufacturing unit is developed on the basis of the models of its sensors and actuators, in Discrete Event System (DES) form. The safe behavior of the unit is expressed in the form of nine rules. The rules are translated into nine regular languages that are realized as a set of proper supervisors. The supervisors are analytically determined and conducted in the open platform FIWARE, using all necessary smart data models and platform tools. © 2024 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：