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8th International Symposium on Parallel architectures, algorithms, and Programming (PAAP)

作者： Xu, Wenchao Liu, Yanbo Yang, Yanqin Ning, Xiaoshuang Chu, Tianxing Song, Hongzhi East China Normal Univ Shanghai Peoples R China Texas A&M Univ Corpus Christi Corpus Christi TX 78412 USA

ISBN: (纸本)9789811064425;9789811064418

This paper presents a stable double-wireless-wearable-band platform that can detect hand gestures. The real-time monitoring and control system utilizes an MCU processor, a wireless transceiver, and a commercial three-axis, digital-output MEMS accelerometer. To detect the user's hand movements, a 3D virtual environment is created via a double-wearable-band controller. Compared with a single wearable band, double wearable bands can identify more gestures with improved stability. Performances in terms of control and detection are discussed in detail. This research development allows the user to specify desired two-hand postures using the multi-sensor information fusion technique for controlling a variety of robotic devices. In the system, the defined two-hand postures also allow the user to add freestyle control to various applications, which bridge the communication gap between humans and the systems. Moreover, the integration of the action recognition algorithm of the combination of two bracelets and the server brings out a real-time approach to analyze and make decisions based on the users' data. Therefore, the system can call for help in a timely manner under critical conditions.

关键词： Double wearable wireless band platform Multiple kalman filter fusion Cloud monitoring health platform

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Point Cloud Processing algorithms for Environment Understanding in Intelligent vehicle applications

Point Cloud Processing Algorithms for Environment Understand...

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作者： Cheikh Sidiya Ahmed West Virginia University Statler College of Engineering & Mineral Resources

学位级别：M.S.

Understanding the surrounding environment including both still and moving objects is crucial to the design and optimization of intelligent vehicles. In particular, acquiring the knowledge about the vehicle environment could facilitate reliable detection of moving objects for the purpose of avoiding collisions. In this thesis, we focus on developing point cloud processing algorithms to support intelligent vehicle applications. The contributions of this thesis are ***, inspired by the analogy between point cloud and video data, we propose to formulate a problem of reconstructing the vehicle environment e.g., terrains and buildings) from a sequence of point cloud sets. Built upon existing point cloud registration tool such as iterated closest point ICP), we have developed an expectation-maximization EM)-like technique that can automatically mosaic multiple point cloud sets into a larger one characterizing the still environment surrounding the ***, we propose to utilize the color information from color images captured by the RGB camera) as a supplementary source to the three-dimensional point cloud data. Such joint color and depth representation has the potential of better characterizing the surrounding environment of a vehicle. Based on the novel joint RGBD representation, we propose training a convolution neural network on color images and depth maps generated from the point cloud ***, we explore a sensor fusion method that combines the results given by a Lidar based detection algorithm and vehicle to everything v2X) communicated data. Since Lidar and v2X respectively characterize the environmental information from complementary sources, we propose to get a better localization of the surrounding vehicles by a linear sensor fusion method. The effectiveness of the proposed sensor fusion method is verified by comparing detection error profiles.

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A new multi-sensor fusion algorithm based on the Information Filter framework

A new multi-sensor fusion algorithm based on the Information...

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Seminar on Detection Systems architectures and Technologies (DAT)

作者： Ammar Cherchar Messaoud Thameri Adel Belouchrani Ecole Supérieure Ali CHABATI Réghaia Algeria Ecole Nationale Polytechnique Algiers Algeria

ISBN: (纸本)9781509045099

his paper presents a new efficient track-to-track fusion (T2TF) algorithm based on the Information Filter (IF) framework which takes into account phenomena encountered in practical applications. In fact, it combines a modified version of the IF framework and a self-tuning fusion procedure based on likelihood functions to address issues such as the correlation of the estimates, the transmission shortcomings and the measurement origin uncertainty. The proposed method is evaluated through simulations and the obtained results show that the proposed algorithm performs as well the optimal centralized fusion schema in an idealized environment while it exhibits better robustness capabilities than existing decentralized algorithms when observation origin uncertainty is considered. Moreover, its reduced complexity cost is suitable for real time applications.

关键词： Microwave measurement Antenna measurements Microstrip antenna arrays Antenna radiation patterns Microwave antenna arrays

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Performance Analysis of End-to-End sensor-to-Cloud Personal Living Platform 8

Performance Analysis of End-to-End Sensor-to-Cloud Personal ...

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8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) / 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH)

作者： Goleva, Rossitza Stainov, Rumen Kletnikov, Nikola Achkoski, Jugoslav Mirtchev, Seferin Ganchev, Ivan Savov, Aleksandar Tech Univ Sofia Comicon Ltd Dept Commun Networks Kl Ohridski Blvd 8 Sofia 1756 Bulgaria Univ Appl Sci Appl Comp Sci Dept Fulda Germany Ss Cyril & Methodius Univ Mil Acad Gen Mihailo Apostolski Skopje Fac Comp Sci & Engn Dept Secur Crisis Protect & RequeueFYROM Skopje Macedonia Univ Limerick Limerick Ireland Univ Plovdiv Paisii Hilendarski Plovdiv Bulgaria Comicon Ltd Mladost 4AL Paskalev StrBitov kombinatFl 2 Sofia 1715 Bulgaria

This paper presents a performance analysis of the end-to-end sensor-to-cloud personal living platform. The analysis is based on a typical architecture starting from a single sensor and actuator and continuing to the virtualized services at smart dust, dew, fog and cloud level. The system is diverse and allows interconnection of different sensors/ actuators technologies directly or throughout gateways. The experiments in a living lab presented use energy harvesters and ZigBee PRO sensors. The results from sensor network are applicable for non-real-time and non-critical data connection. As a final conclusion, we claim that for critical and non-critical measurements that need to be supported in a typical living environment there is a necessity to use different priorities of the services and different sensors as well. (c) 2017 The Authors. Published by Elsevier B.v.

关键词： sensor technology cloud performance analysis living lab non-real-time communication critical and non-critical data

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v2v-Communication, LiDAR System and Positioning sensors for Future fusion algorithms in Connected vehicles

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Transportation Research Procedia 2017年 27卷 69-76页

作者： Sven Eckelmann Toralf Trautmann Hagen Ußler Benjamin Reichelt Oliver Michler Hochschule für Technik und Wirtschaft Dresden Friedrich-List-Platz 1 01069 Dresden Germany Technische Universität Dresden Hettnerstraße 3 01062 Dresden Germany

The automotive industry is changing from conventional driving into connected and later on autonomous driving. The fundamental principle of this alteration is communication and exchange of data between vehicles and other kind of traffic objects, for example traffic lights. The knowing about basic conditions from all traffic objects within a close proximity can ensure a more precise reaction of Advanced Driver Assistant Systems (ADAS). Thereby vehicle-to-vehicle (v2v) technology contributes to increase traffic safety. This paper describes an investigation of v2v communication based on commercial On-Board-Units (OBU). These units, integrated in two test-vehicles, transmit and receive data based on the IEEE 802.11p standard (ETSI ITS-G5). The messages include basic conditions like position, motion vector and vehicle configuration parameters. Those information ensure a relative positioning which is also implemented in the paper on hand. The calculations provide the prerequisites for additional autonomous vehicle system applications like autonomous braking or steering maneuver. To improve precision and reliability of ADAS, statements about integrity are inevitable. These can be achieved by a fusion of different sensor information. Therefore the paper also presents possibilities to ensure an accurate localization and object detection, regarding a Light Detection and Ranging (LiDAR) System (velodyne vLP-16) and an Differential Global Positioning System (DGPS) approach. The interaction of communication, sensor fusion algorithms and integrity considerations form the basis for autonomous driving.

关键词： Autonomous Driving Connected vehicle v2v-Communication IEEE 802.11p Relative Positioning Object Detection sensor fusion

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Performance evaluation on contour extraction using Hough transform and RANSAC for multi-sensor data fusion applications in industrial food inspection

Performance evaluation on contour extraction using Hough tra...

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20th IEEE Conference on Signal Processing - algorithms, architectures, Arrangements, and applications (SPA)

作者： Kroeger, M. Sauer-Greff, W. Urbansky, R. Lorang, M. Siegrist, M. Univ Kaiserslautern Chair Commun Engeneering Kaiserslautern Germany WIPOTEC GmbH Kaiserslautern Germany

ISBN: (纸本)9788362065271

For multi-sensor data fusion applications the accurate alignment of different sensor data is essential for the proper combination of matching features. In food inspection system the boxing often is in a rectangular shape. This knowledge can be used to rectify the image data, an important step in the alignment stage. In case of low contrast between boxing and background, the detected contour may differ significantly from the actual values. In this paper the performance of the Hough transform and the RANdom SAmple Consensus (RANSAC)-algorithm are evaluated relating to the correct extraction of the boxing contour out of contour data distorted by position errors of the outer shape. The evaluation results indicate the superiority of the RANSAC algorithm with respect to scalability, robustness and execution time.

关键词： Hough transforms

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PASES: Combining radar and video sensing for improved pedestrian safety

PASES: Combining radar and video sensing for improved pedest...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Chenault, David B. Edmondson, Richard P. Polaris Sensor Technol Inc 200 West Side SqSuite 320 Huntsville AL 35801 USA

ISBN: (纸本)9781510601130

Polaris sensor Technologies reports on the development of Pedestrian Automated System for Enforcement and Safety (PASES), a radar and video based system used to monitor vehicle and pedestrian traffic with the intent of improving pedestrian safety. Data is fused from a system of multiple sensors and multiple sensor modalities to identify vehicular violations of pedestrian right of way. A focus was placed on the selection of low cost COTS sensors to make the system more widely available to state and local DOTs with limited budgets. applications include automated enforcement, adaptive traffic control, and improved intersection and crosswalk design based on high quality data available for traffic engineering. We discuss early results with high fidelity sensors, and the performance trades made in order to make the system affordable. A discussion of the system processing architecture is included which highlights the treatment of each sensor data type, and the means of combining the processed data products into state information related to traffic incidents involving vehicles and pedestrians.

关键词： Pedestrian radar video tracking sensor fusion

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In-Drilling Alignment Scheme for Borehole Assembly Trajectory Tracking over a Wireless Ad hoc Network

In-Drilling Alignment Scheme for Borehole Assembly Trajector...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Odei-Lartey, E. Hartmann, K. Univ Siegen ZESS Zentrum Sensorsyst Paul Bonatz Str 9-11 D-57076 Siegen Germany

ISBN: (纸本)9781510601130

This paper describes the feasibility and implementation of an In-drilling alignment method for an inertia navigation system based measurement while drilling system as applied to the vertical drilling process, where there is seldom direct access to a reference measurement due the communication network architecture and telemetry framework constraints. It involves the sequential measurement update of multiple nodes by the propagation of the reference measurement sequentially over nodes, each of which has an integrated inertia measurement unit sensor and runs the extended Kalman filter based signal processing unit, until the final measurement update of the main sensor node embedded in the borehole assembly is done. This is done particularly to keep track of the yaw angle position during the drilling process.

关键词： In-drilling alignment extended Kalman filter inertial navigation system vertical drilling measurement update sensor node low-cost IMU gyroscope

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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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Optimal Rotation Sequences for Active Perception

Optimal Rotation Sequences for Active Perception

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Nakath, David Rachuy, Carsten Clemens, Joachim Schill, Kerstin Univ Bremen Cognit Neuroinformat D-28359 Bremen Germany

ISBN: (纸本)9781510601130

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft.

关键词： Markov decision process manifold representation particle filter value iteration multi-sensor fusion optimal decision making active perception information gain

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