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

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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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Human-Based Gait Authentication Using Multi-modal sensors at the Tactical Edge Device: Smartphone 6

Human-Based Gait Authentication Using Multi-modal Sensors at...

引用

conference on Big Data vi - Learning, Analytics, and applications

作者： Sandrakumar, Shageenth Khan, Simon Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781510673915;9781510673908

The Department of Defense (DoD) including the US Air force have been seeing increased physical security risks, such as gate runners, active shooter situations, and other use cases (such as Drone ISR, Rapid Deployment, Force Protection, and Security Force), requiring increased coordination and data cooperation. Additionally, technology and operational environments are getting more complex, interconnected and diverse. Recently a team of developers developed a plug-in for the Android Team Awareness Kit (ATAK). This plug-in analyzes sensor data from tactical edge device's (e.g., cell phone) onboard accelerometer and gyroscope to determine the movement of a person when they walk. The plug-in also uses machine learning (ML) algorithms to create a model of that person's gait, and then sends pertinent data through the associated human gait model to authenticate a user. The novelty of our effort lies into enhancing this human gait authentication by using different features extracted from spectral information of the accelerometer and gyroscope signals from the smartphone using a public human activity recognition dataset (WISDM) as a proof of concept, marking a previously unexplored approach. By leveraging spectral data, we seek to enhance the accuracy and robustness of authentication systems in military contexts. After the feature extraction is performed, Kernal Discriminant Analysis (KDA) is utilized to reduce the dimensions of the spectral features to 50;after including the non-spectral features, our total number of final features becomes 65. After adding the total features, we perform feature-level fusion utilizing ML algorithms and the performance shows promising for authentication utilizing 51 users. The SVM-rbf classifiers achieved a mean Equal Error Rate (EER) and mean Accuracy (ACC) of 2% and 97.3%, while the GBM classifiers achieved a mean EER and ACC of 0.4% and 99.1%, and the CNN classifiers achieved a mean EER and ACC of 10% and 90.4% respectively.

关键词： Machine Learning Spectral Feature Extraction Spectogram Gait Welch's Method Envelope Power Spectrum Kernel Discriminant Analysis Feature-level fusion

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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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An iToF/Triangulation Depth sensor for Mixed Reality applications 6

An iToF/Triangulation Depth Sensor for Mixed Reality Applica...

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6th conference on Optical architectures for Displays and Sensing in Augmented, virtual, and Mixed Reality-AR, VR, MR

作者： Godbaz, John P. Zhu, Ling Mogallapu, vishali Poostchi, Mahdieh Gullapalli, Jay Oh, Jerry Li Minseok Santos, Jonathan Karicherla, Annapurna Mehta, Swati Morales, Lucas Perry, Travis Rendon, Kyle Roland, Brock Sutherland, Reid Microsoft Corp 1045 Avenida St Mountain View CA 94043 USA

ISBN: (纸本)9781510686069;9781510686076

This paper presents a prototype two-in-one, dense-plus-sparse depth module designed for Mixed Reality headsets that uses a novel approach to sparse depth imaging by combining indirect Time-of-Flight (iToF) and triangulation modalities to provide improved range and accuracy. The module uses an ADI ADSD3030 VGA iToF sensor and reduces module size from 62 x 24 x 13 mm in HoloLens 2 to 33.5 x 15 x 7.2 mm. Sparse frames have temporal noise of <1% of distance at 3% reflectivity, 3 klx sunlight equivalent spectrum and can image 95% reflectivity targets out to the ambiguity distance of 21 m while consuming 14.7 mJ per-frame. New low-compute algorithms that combine iToF and triangulation are presented and are demonstrated to mitigate systematic errors such as multipath and subsurface diffusion as well as extend dynamic range under full-sunlight and high-signal conditions. sensor applications include scene understanding, object capture and hand-tracking.

关键词： Depth Mixed Reality Time of Flight Indirect Time of Flight iToF Lidar Triangulation Structured Light

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Whose Data are Reliable: sensor Declared Data Reliability 19

Whose Data are Reliable: Sensor Declared Data Reliability

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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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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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