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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications III"

共 369 条记录，以下是1-10 订阅

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Optimizing Long-Term Robot Tracking with Multi-Platform sensor fusion

Optimizing Long-Term Robot Tracking with Multi-Platform Sens...

引用

IEEE/CVF Winter conference on applications of Computer Vision (WACV)

作者： Albanese, Giuliano Mitra, Arka Zaech, Jan-Nico Zhao, Yupeng Chhatkuli, Ajad Van Gool, Luc Swiss Fed Inst Technol Zurich Switzerland Katholieke Univ Leuven Leuven Belgium INSAIT Sofia Bulgaria

ISBN: (纸本)9798350318920;9798350318937

Monitoring a fleet of robots requires stable long-term tracking with re-identification, which is yet an unsolved challenge in many scenarios. One application of this is the analysis of autonomous robotic soccer games at RoboCup. Tracking in these games requires handling of identically looking players, strong occlusions, and non-professional video recordings, but also offers state information estimated by the robots. In order to make effective use of the information coming from the robot sensors, we propose a robust tracking and identification pipeline. It fuses external non-calibrated camera data with the robots' internal states using quadratic optimization for tracklet matching. The approach is validated using game recordings from previous RoboCup World Cup tournaments.

关键词： algorithms algorithms and algorithms applications formulations Machine learning architectures Robotics Video recognition and understanding

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DSP architectures of Covariance Intersection fusion Algorithm for Automotive sensor fusion 14

DSP Architectures of Covariance Intersection Fusion Algorith...

引用

14th International conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Praharshita, D.S.L. Achala, G. Srihari, Pathipati Acharya, U. Shripathi Pardhasaradhi, Bethi India National Institute of Technology Karnataka ECE Dept. India Continental Autonomous Mobility India Pvt Ltd Adas Dept. India

ISBN: (纸本)9798350335095

The data fusion from sensors within the automotive vehicle is vital for improved accuracy and safety. The centralized and information matrix fusion (IMF) algorithms are famous for providing an optimal fusion estimate. However, the IMF is not viable in automotive sensor fusion applications due to the limited bandwidth and low hardware resources. Hence, distributed fusion technology is widely adopted in the automotive sensor applications to achieve high-speed and low-area realizations. This paper proposes three digital signal processing (DSP) architectures for covariance intersection (CI) fusion algorithm: Pipelined-traditional CI, adder-ladder CI, and pipelined adder-ladder CI. The proposed DSP architectures are evaluated with hardware resource consumption (multipliers, adders, and delays), maximum achievable frequency, and latency of the architecture. In addition, proposed CI algorithms for Digital Signal Processing (DSP) architectures are compared with IMF DSP architectures. The hardware resources and optimal pipeline stages required for CI with respect to N number of sensors are provided. The traditional pipeline algorithm requires N number of stages where as the proposed pipelined version of adder-ladder CI requires a N-1 pipeline stage with additional 7N-1 and 7N-3 delay elements for even and odd number of sensors to achieve the overall system operating frequency to an operation of multiplier. The proposed DSP architectures are suitable for automotive sensor fusion due to their high operating frequency and low hardware resources. © 2023 IEEE.

关键词： Digital signal processing

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MULTI-sensor INFORMATION fusion TECHNOLOGY: PRINCIPLE, applications AND KEY TECHNOLOGIES EXPLORATIONS 2

MULTI-SENSOR INFORMATION FUSION TECHNOLOGY: PRINCIPLE, APPLI...

引用

2nd International conference on Mechatronic Automation and Electrical Engineering, ICMAEE 2024

作者： Wu, Wenchen Xu, Ruizhe Guangdong Country Garden School Foshan528312 China The Affiliated Middle School of Fujian Normal University Fuzhou350007 China

ISBN: (纸本)9781837242672

Multi-sensor information fusion (MSIF) has emerged as a critical technology in various fields due to the growing complexity of systems and the demand for precise information. This paper explores the fundamental principles, key technologies, and potential applications of MSIF. The paper delves into the design and implementation of MSIF systems, discussing various system architectures such as centralized, distributed, and hybrid models. Key technologies crucial to MSIF, including sensor calibration, data association, filtering methods, and fusion algorithms like Bayesian Criterion, Dempster-Shafer Evidence Theory, Fuzzy Theory, and Neural Networks, are thoroughly examined. The study highlights the importance of data preprocessing and feature extraction techniques in achieving efficient data fusion. Furthermore, the potential of MSIF in diagnosing complex systems is demonstrated through applications in industrial automation, environmental monitoring, and healthcare. MSIF also faces challenges related to data synchronization, algorithm complexity, and the integration of diverse data sources. With ongoing advancements in sensor technology and data processing, MSIF is poised to play an increasingly significant role in intelligent systems, including autonomous vehicles and smart cities. © The Institution of Engineering & Technology 2024.

关键词： Information fusion

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Comparative Analysis and Implementation of Energy-Quality Scalable Multiply-Accumulate architectures for TinyML applications 31

Comparative Analysis and Implementation of Energy-Quality Sc...

引用

31st conference on Electronics Circuits and Systems

作者： Pelayo, Kenn Danielle C. Alvarez, Anastacia B. Chua, Adelson N. Galapon, Fredrick Angelo R. Tan, Allen Jason A. Quizon, Lawrence Roman A. Univ Philippines Diliman Elect & Elect Engn Inst Quezon City Philippines

ISBN: (纸本)9798350377217;9798350377200

Recent trends in machine learning algorithms have shifted from computer vision applications to near-sensor intelligent data analytics, such as wireless sensor nodes, which are considered as ultra-low power devices. This shift presents new challenges in energy consumption, throughput, and area budgets. This work implements and optimizes Bit fusion, a 2D-scalable divide-and-conquer (D&C) MAC architecture with precision-scaling from 8 to 2 bits, through bitwidth optimizations and by trading-off complexity overheads that are not aligned with the target MobileNet-v2 model. The designs are synthesized using 22-nm FD-SOI CMOS technology. It was determined that the throughput trade-offs of 1-level architectures in 2bx2b mode for 17.37% less energy per operation and 26.84% more throughput per area would be preferred. Architecture variations were also explored wherein sum-together (ST) architectures outperformed sum-apart (SA) architectures with 21.03% reduction in energy per operation and 33.32% increase in throughput per area.

关键词： ASIC deep neural networks digital accelerators multiply-accumulate MAC precision-scalable circuits energy-quality scalable circuits

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Data fusion in Wireless sensor Network: An Overview

Data Fusion in Wireless Sensor Network: An Overview

引用

2023 IEEE CHILEAN conference on Electrical, Electronics Engineering, Information and Communication Technologies, ChileCon 2023

作者： Bernal, Daniel Fernando Quintero Kaschel, Hector Kern, John Universidad de Santiago de Chile Departamento de Ingeniería Eléctrica Santiago Chile

ISBN: (纸本)9798350369533

Due to the massive increase in data sets in contemporary applications and the difficulty of their processing in various approaches, data fusion remains a predominant way to obtain outstanding results, in terms of reliability, efficiency, and precision. The following document presents an overview of data fusion in wireless sensor networks;in which, various concepts to applications are considered to generate a base document for future research. This article gives a comprehensive and current view of models or architectures, techniques, methodologies or algorithms, and a current review of applications in different areas. © 2023 IEEE.

关键词： Wireless sensor networks

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Whose Data are Reliable: sensor Declared Data Reliability 19

Whose Data are Reliable: Sensor Declared Data Reliability

引用

19th International conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Shafin, Sakib Shahriar Karmakar, Gour Mareels, Iven Balasubramanian, Venki Kolluri, Ramachandra Rao Federat Univ Australia Ctr Smart Analyt CSA Ballarat Vic 3350 Australia Federat Univ Australia Inst Innovat Sci & Sustainabil Ballarat Vic 3350 Australia IBM Australia Pty Ltd IBM Consulting St Leonards Australia

ISBN: (纸本)9798350336672

sensor data is susceptible to faults, noise, and malicious attacks, posing a significant operational and security threat. Therefore, ensuring reliability of sensor data is critical for real-time monitoring systems. Prior research on sensor data reliability relies on edge or upper-layer devices for data fusion from multiple sensors, employing architectures with major overheads and latency due to transmission and storage demands. An alternative approach is to have the sensor estimate and declare its own reliability. While some methods involve sensors computing data confidence and including it in payloads, limitations arise in the absence of neighboring sensor data, and communication overheads are incurred. To address this problem, this paper proposes an innovative approach to enhance the reliability of sensor data using an intelligent self-declaration process. Proposed reliability estimation is evaluate with three lightweight estimation algorithms, namely, Kalman Filter, Holt-Winters Method, and Mahalanobis Distance using sensor's historical data. The reliability level is then added to the three reserved bits of a TCP packet header which results in zero additional overhead. Experiments conducted using real-world sensor data (from water quality monitoring systems) obtained from our IoT lab demonstrate the effectiveness of our proposal and the potential for application in real-world sensor-based applications.

关键词： Reliability

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Resource-Efficient sensor fusion via System-Wide Dynamic Gated Neural Networks 21

Resource-Efficient Sensor Fusion via System-Wide Dynamic Gat...

引用

21st Annual IEEE International conference on Sensing, Communication, and Networking, SECON 2024

作者： Singhal, C. Wu, Y. Malandrino, F. de Guevara Contreras, S. Ladron Levorato, M. Chiasserini, C.F. INRIA France UC Irvine United States CNR-IEIIT Italy CNIT Italy Politecnico di Torino Italy Chalmers University of Technology Sweden

ISBN: (纸本)9798331519186

Mobile systems will have to support multiple AI-based applications, each leveraging heterogeneous data sources through DNN architectures collaboratively executed within the network. To minimize the cost of the AI inference task subject to requirements on latency, quality, and - crucially - reliability of the inference process, it is vital to optimize (i) the set of sensors/data sources and (ii) the DNN architecture, (iii) the network nodes executing sections of the DNN, and (iv) the resources to use. To this end, we leverage dynamic gated neural networks with branches, and propose a novel algorithmic strategy called Quantile-constrained Inference (QIC), based upon quantile-Constrained policy optimization. QIC makes joint, high-quality, swift decisions on all the above aspects of the system, with the aim to minimize inference energy cost. We remark that this is the first contribution connecting gated dynamic DNNs with infrastructure-level decision making. We evaluate QIC using a dynamic gated DNN with stems and branches for optimal sensor fusion and inference, trained on the RADIATE dataset offering Radar, LiDAR, and Camera data, and real-world wireless measurements. Our results confirm that QIC matches the optimum and outperforms its alternatives by over 80%. © 2024 IEEE.

关键词： Constrained optimization

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A Flexible sensor Based on PVC Gel for Detections of Robotic Grasping 17th

A Flexible Sensor Based on PVC Gel for Detections of Robotic...

引用

17th International conference on Intelligent Robotics and applications

作者： Zhong, Qiyun He, Qingsong Xie, Lin Shi, Ziyan Nanjing Univ Aeronaut & Astronaut Jiangsu Prov Key Lab Bion Funct Mat Coll Mech & Elect Engn Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Adv Technol Small & Medium Sized UAV Minist Ind & Informat Technol Unmanned Aerial Vehicles Res Inst Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Aerosp Struct Nanjing 210016 Peoples R China

ISBN: (纸本)9789819607945;9789819607952

The rapid evolution of the smart industry has propelled significant advancements in both the realms of flexible electronics and robotics. The fusion of flexible sensing with intelligent robots bestows upon them the capability of tactile sensing, a critical enhancement that elevates their intelligence, digitalization, and practical applicability. We have triumphantly developed an innovative poly(vinyl chloride)/multi-walled carbon nanotubes polymer gel (PVC/MWCNTs polymer gel, PMPG), renowned for its exceptional elasticity and sensitivity. This high-performing sensing gel was crafted through a physical cross-linking method, utilizing poly(vinyl chloride) as the base matrix and multi-walled carbon nanotubes as the reinforcing fillers. Optimally, at a PVC:DBA = 1:5 (1 wt% of MWCNTs), PMPG demonstrates a remarkable response time of merely 172 ms, coupled with the capacity for sustained, continuous measurements. The material's stability is commendable, enduring up to 2,500 successive measurements without degradation. By integrating PMPG with machine learning algorithms, the soft gripper is endowed with enhanced tactile sensing and responsive feedback capabilities, heralding a new era for soft robotics across diverse settings.

关键词： Flexible sensor PMPG Tactile Sensing

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DSP architectures of Covariance Intersection fusion Algorithm for Automotive sensor fusion

DSP Architectures of Covariance Intersection Fusion Algorith...

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International conference on Computing and Networking Technology (ICCNT)

作者： D.S.L. Praharshita Achala G Pathipati Srihari U. Shripathi Acharya Bethi Pardhasaradhi Engineering Development Group (EDG) India ECE Dept. National Institute of Technology Karnataka India ADAS Dept. Continental Autonomous Mobility India Pvt Ltd India

The data fusion from sensors within the automotive vehicle is vital for improved accuracy and safety. The centralized and information matrix fusion (IMF) algorithms are famous for providing an optimal fusion estimate. However, the IMF is not viable in automotive sensor fusion applications due to the limited bandwidth and low hardware resources. Hence, distributed fusion technology is widely adopted in the automotive sensor applications to achieve high-speed and low-area realizations. This paper proposes three digital signal processing (DSP) architectures for covariance intersection (CI) fusion algorithm: Pipelined-traditional CI, adder-ladder CI, and pipelined adder-ladder CI. The proposed DSP architectures are evaluated with hardware resource consumption (multipliers, adders, and delays), maximum achievable frequency, and latency of the architecture. In addition, proposed CI algorithms for Digital Signal Processing (DSP) architectures are compared with IMF DSP architectures. The hardware resources and optimal pipeline stages required for CI with respect to N number of sensors are provided. The traditional pipeline algorithm requires N number of stages where as the proposed pipelined version of adder-ladder CI requires a N−1 pipeline stage with additional 7N−1 and 7N−3 delay elements for even and odd number of sensors to achieve the overall system operating frequency to an operation of multiplier. The proposed DSP architectures are suitable for automotive sensor fusion due to their high operating frequency and low hardware resources.

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Multi-sensor information fusion technology: principle, applications and key technologies explorations

Multi-sensor information fusion technology: principle, appli...

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2nd International conference on Mechatronic Automation and Electrical Engineering (ICMAEE 2024)

作者： Wenchen Wu Ruizhe Xu Guangdong Country Garden School Foshan 528312 People's Republic of China The Affiliated Middle School of Fujian Normal University Fuzhou 350007 People's Republic of China

ISBN: (数字)9781837242672

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