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PERCEPT: a sophisticated experimental set-up dedicated to heterogeneous sensor fusion

PERCEPT: a sophisticated experimental set-up dedicated to he...

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International conference on Industrial Electronics, Control and Instrumentation

作者： O. Dessoude C. Olivier B. Zavidovique Laboratoire Système de Perception ETCA Arcueil France

The study of perception, an essential function for autonomous robotics, has led to new developments in the fields of modeling, stochastic data processing, and control. The authors describe a surveillance robot dedicated to heterogeneous data fusion algorithms' implementation and real-size real-time testing, which has become necessary to validate these emerging techniques in a realistic environment. This robot holds various sensors mounted on rotational units and provides a multi-degree-of-freedom command. The design includes original distributed hardware and software architectures encompassing the specific data processing, fusion, and feedback control. Modularity and a user-friendly interface allow easy design of perception control applications.< >

关键词： Robot sensing systems Data processing Stochastic processes Process control Surveillance Testing Hardware Software architecture Feedback control Application software

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In-network stochastic consensus for WSN surveillance applications

In-network stochastic consensus for WSN surveillance applica...

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International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Cristian Dragana Viorel Mihai Grigore Stamatescu Dan Popescu Department of Automatic Control and Industrial Informatics University Politehnica of Bucharest Bucharest Romania

Surveillance applications require reliable monitoring system architectures and cost-efficient innetwork data processing mechanisms able to provide effective information extraction for event tracking. Wireless sensor Networks (WSNs) appear to be the most suitable technology due to some well known benefits and the rapid development of embedded devices. Current research is mostly focused on improving and developing new decentralized sensor fusion schemes able to overcome the limitations introduced by the battery operated sensor nodes, but most of the time evaluating the proposed algorithms is performed with a serious lack of precise channel modeling. To close this gap, we provide a stochastic consensus implementation for lossy wireless networks comprising fixed and mobile sensor nodes, as a heterogeneous surveillance system based on ground sensor nodes and UAVs (Unmanned Aerial Vehicles). We developed a simulation framework tailored for fixed and mobile sensor nodes and we are able to evaluate the performance of consensus algorithms from a comparative standpoint, considering deterministic and probabilistic packet propagation models described by common models such as Free Space and Nakagami models. In this paper, we consider a complex in-network adaptive estimation using the distributed least-mean square algorithm tailored for WSN. We perform a mean-square error (MSE) performance analysis for both deterministic and probabilistic propagation models.

关键词： Wireless sensor networks Wireless communication Probabilistic logic Surveillance Adaptation models Bridges Stochastic processes

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Experimental characterization of synchronization protocols for wireless networks

Experimental characterization of synchronization protocols f...

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IEEE International Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems (VECIMS)

作者： M. De Santo L. Ferrigno V. Paciello A. Pietrosanto DIIIE University of Salerno Fisciano SA Italy DAEIMI University of Cassino Cassino FR Italy

Nowadays more and more measurement applications where sensor nodes cooperate to realize a data fusion process are entrusted to wireless sensor networks (WSN). Data fusion to be accurate requires that nodes be referred to a common clock and among themselves. In this scenario node synchronization got a crucial research topic and even sophisticated synchronization algorithms can be easily found in literature. Not a few others show to be especially designed for low cost, low memory and low power architectures. Their performance is usually evaluated either through analytical considerations or in simulation environments, but in some cases where ad hoc radio systems have been adopted. This paper makes a first step toward an experimental characterization of synchronization protocols that hold into account also influence factors which arise when commercial wireless communication busses as WiFi, BlueTooth (BT), ZigBee are adopted.

关键词： Synchronization Wireless communication Wireless sensor networks Ad hoc networks Protocols Instruments Probability density function

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

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

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IEEE International conference on Electronics, Circuits and Systems (ICECS)

作者： Kenn Danielle C. Pelayo Anastacia B. Alvarez Adelson N. Chua Fredrick Angelo R. Galapon Allen Jason A. Tan Lawrence Roman A. Quizon Electrical and Electronics Engineering Institute University of the Philippines - Diliman Quezon City Philippines

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

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 precisionscaling 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 $\mathbf{2 b} \times 2 \ \text{b}$ mode for $\mathbf{1 7. 3 7 \%}$ less energy per operation and $\mathbf{2 6. 8 4 \%}$ more throughput per area would be preferred. Architecture variations were also explored wherein sum-together (ST) architectures outperformed sum-apart (SA) architectures with $\mathbf{2 1. 0 3 \%}$ reduction in energy per operation and $\mathbf{3 3. 3 2 \%}$ increase in throughput per area.

关键词： Wireless communication Semiconductor device modeling Wireless sensor networks Quantization (signal) Tiny machine learning Computer architecture Throughput CMOS technology Complexity theory Reliability

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On the fusion and transference of knowledge. I

On the fusion and transference of knowledge. I

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IEEE International conference on Information Reuse and Integration (IRI)

作者： S.H. Rubin SPAWAR Systems Center San Diego CA USA

Contemporary neural architectures having one or more hidden layers suffer from the same deficiencies that genetic algorithms and methodologies for non-trivial automatic programming do; namely, they cannot exploit inherent domain symmetries for the transference of knowledge from an application of lesser to greater rank, or across similar applications. As a direct consequence, no ensemble of contemporary neural architectures allows for the effective codification and transference of knowledge within a society of individuals (i.e., swarm knowledge). These deficiencies stem from the fact that contemporary neural architectures cannot reason symbolically using heuristic ontologies. They cannot directly provide symbolic explanations of what was learned for purposes of inspection and verification. Moreover, they do not allow the knowledge engineer to precondition the internal feature space through the application of domain-specific modeling languages. A symbolic representation can support the heuristic evolution of an ensemble of neural architectures. Each neural network in the ensemble imbues a hidden layer and for this reason is NP-hard in its learning performance. It may be argued that the internal use of a neat representation subsumes the heuristic evolution of a scruffy one. It follows that there is a duality of representation under transformation. The goal of AI then is to find symbolic representations, transformations, and associated heuristic ontologies. This paper provides an introduction to this quest. Consider the game of chess for example. If a neural network or symbolic heuristic is used to evaluate board positions, then the best found iterate (i.e., of weights or symbols) serves as a starting point for iterative refinement. This paper addresses the ordering and similarity of the training instances in refining subsequent iterates. If we fix the learning technology, then we need to focus on reducing the problem, composing intermediate results, and transferring th

关键词： Neural networks Ontologies Genetic algorithms Automatic programming Inspection Knowledge engineering Machine learning sensor phenomena and characterization USA Councils Domain specific languages

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A multi-sensor integration method of signals in a metal cutting operation via application of multilayer perceptron neural networks

A multi-sensor integration method of signals in a metal cutt...

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Fifth International conference on Artificial Neural Networks (Conf. Publ. No. 440)

作者： D.E. Dimia P.M. Lister N.J. Leighton Eng. Res. Group Univ. of Wolverhampton UK Engineering Research Group SEBE University of Wolverhampton UK

The potential application of neural networks in manufacturing scenarios is increasingly becoming feasible. Typical of such manufacturing scenario is the integration of metal cutting sensor signals in pursuance of reliable tool condition monitoring (TCM) system. Successful application of this method of sensor integration could save downtime and costs, that would otherwise not have been realised through traditional tool changing philosophies. Unfortunately, the network algorithms used have complicated, requiring detailed sensor signal pre-processing. Partly as a consequence, developed systems have found very limited applications to-date. In this paper, the authors present a simple sensor fusion method via the neural networks approach to the TCM problem. Turning tests were conducted from which the static cutting force, dynamic cutting force and the vibration signature were recorded. The obtained data was used to investigate the classification capability of simple multilayer perceptron (MLP) neural network architectures to the detection of tool wear. Obtained results showed classification accuracy of well over 90%.

关键词： Neural networks

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Research on the System Design and Application of Mobile Manipulator Hybrid Robot for Transporting in Intelligent Factory

Research on the System Design and Application of Mobile Mani...

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Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP), International conference on

作者： Xiaohong Qin Lianhao Zhang Bin Zhao Shenyang Institute of Science and Technology Shenyang China Northeastern University Shenyang China SIASUN Robot & Automation Co. Shenyang China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

Based on the development and application status of mobile manipulator hybrid robot, this paper takes the handling process requirements of intelligent factories in China as the research objective to design and develop a composite robot platform system. The hardware system mainly includes mobile platforms, manipulators, and sensors. The software system mainly consists of control systems, software architectures, algorithm libraries and corresponding communication protocols. This platform system has the key technologies of scene information perception, mobile path planning and self-collision detection of the manipulator during the grasping process, which are necessary in engineering project applications. The corresponding innovative algorithms are embedded in it, and scene tests and effect analysis are carried out in a memory module production factory. Test results show that, compared with mainstream products and application technologies in the field, this mobile manipulator hybrid robot can use multiple sensors to obtain scene information and conduct high-precision data fusion, simultaneously meet multiple measurement indicators of mobile path planning, and quickly achieve pre-collision warning without the application of sensors, verifying the effectiveness and advancement of the independently developed platform system.

关键词： Software architecture Service robots Software algorithms Memory modules sensor fusion Manipulators Robot sensing systems Production facilities Path planning Intelligent sensors

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Whose Data are Reliable: sensor Declared Data Reliability

Whose Data are Reliable: Sensor Declared Data Reliability

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IEEE International conference on Wireless and Mobile Computing, Networking And Communications (WiMob)

作者： Sakib Shahriar Shafin Gour Karmakar iven Mareels Venki Balasubramanian Ramachandra Rao Kolluri Centre for Smart Analytics (CSA) Institute of Innovation Science and Sustainability Federation University Australia Ballarat VIC Australia IBM Consulting IBM Australia Pty Ltd

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.

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Multisensor fusion-based object detection and tracking using Active Shape Model

Multisensor fusion-based object detection and tracking using...

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International conference on Digital Information Management (ICDIM)

作者： Dongeun Lee Sunghoon Choi Information Technology Research Center LG CNS Company Limited Seoul South Korea

This paper proposes automatic target detection and tracking system using Active Shape Model (ASM). Existing model based approaches for tracking are either manually initiated or need some form of user interaction to locate the object in images. Also the low light environmental conditions for surveillance systems make the tracking further harder. Hence the proposed system makes use of multiple sensors in the form of IR and visible cameras to enable tracking in degraded and low light environments. The proposed algorithm consists of the following stages: (i) input image evaluation for obtaining the conditions under which the camera is placed, (ii) an integrated motion detector and target tracker, (iii) active shape tracker (AST) for performing tracking, (iv) update of tracking results for real time tracking of targets. In the first stage the input image is evaluated for the lighting conditions. If the lighting conditions are poor then IR sensor is integrated with the CCD sensor for tracking applications. In the second stage the motion detector and region tracker are used to provide feedback to AST for automatic initialization of tracking. Tracking is carried out in the third stage using ASM. The final stage extracts the parameters and tracking information and applies it to the next frame if the tracking is carried out in real time. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, shape analysis, and model-based coding.

关键词： Shape Training Laplace equations Real time systems Computer vision Target tracking

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