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Active Distance Measurement based on Robust Artificial Markers as a Building Block for a Service Robot Architecture

IFAC Proceedings Volumes 2000年第28期33卷 325-330页

作者： Axel Walthelm Ralf Kluthe Institut für Technische Informatik Medizinische Universität zu Lübeck Ratzeburger Allee 160 D23538 Lübeck Germany

Software architectures for service robots have to support flexible combinations of basic algorithms to form complex goal directed behaviors. This paper presents a building block for an active distance measurement: the Glare Laser Range Scanner Robotics *** setup and the intended functionality of GLaRE are described and the more complex algorithms that form modules within GLaRE will be presented in detail. A artificial visual marker is chosen as a point of attention, for which the distances has to be determined. The detection of the marker is distance and orientation invariant and thus suitable for both experimental and practical applications. The overall architectural design of GLaRE will be described.

关键词： Robot vision sensor fusion Robot control architectures

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\"Found\" in Space - Helical Resonator Filters for Satellite Communication [Book\/Software Reviews]

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IEEE Microwave Magazine 2015年第11期16卷 80-82页

作者： James Chu Kennesaw State University Southern Polytechnic State University Marietta Georgia United States

This book's main objective is to offer a contemporary, comprehensive approach to the design of RF and microwave filters for satellite applications with an emphasis on helical resonator technology. By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies. Complete with research-supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex-optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs. The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help readers broaden their understanding of prospective applications and how to address such problems in practice. After reading the book, readers will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.

关键词： Book reviews Filtering theory Satellite communication Microwave filters Design methodology Wireless sensor networks Radio frequency Information filters Helical antennas

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Wireless structural monitoring for homeland security applications

Wireless structural monitoring for homeland security applica...

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Conference on Nondestructive Detection and Measurement for Homeland Security ii

作者： Kiremidjian, GK Kiremidjian, A Lynch, JP Sensametr Inc Palo Alto CA 94301 USA

ISBN: (纸本)0819453129

This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.);(b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions;(c) peer-to-peer wireless communications for information exchange among units (thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion;(d) ultra low power operation;(e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.

关键词： wireless sensing structural monitoring damage assessment homeland security

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Reviewing the process of data fusion in wireless sensor network: A brief survey

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International Journal of Wireless and Mobile Computing 2015年第2期8卷 130-140页

作者： Shivaprasad Yadav, S.G. Chitra, A. Lakshmi Deepika, C. Department of Telecommunication Engineering M.S. Ramaiah Institute of Technology Bangalore Karnataka India Department of Computer Applications P.S.G College of Technology Coimbatore Tamil Nadu India Department of Biomedical Engineering P.S.G College of Technology Coimbatore Tamil Nadu India

Wireless sensor network is deployed on human inaccessible region to perform a very sensitive task where various external and internal factors affect the results being accumulated by the sensing node. Data fusion is one such technique. With the upcoming applications of wireless sensor network, it is also accompanied by various power and quality related issues. However, it was seen that whatever are the challenges or issues, it affects basically the data collection techniques from sensor nodes and corresponding forwarding to sink node. Hence, this paper aims to perform an exclusive investigation of the data fusion with respect to various standard architectures, standard algorithms and techniques investigated in the past study for performing data fusion, followed by open issues and research gap in the existing system adopted for enhancing the efficiency of data fusion techniques. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： sensor nodes

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Leveraging provenance to improve data fusion in sensor networks

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Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Dogan, Gulustan Seo, Eunsoo Brown, Theodore Abdelzaher, Tarek F. City University of New York United States University of Illinois at Urbana Champaign United States

ISBN: (纸本)9780819490858

Provenance is the information about the origin of the data inputs and the data manipulations to a obtain a final result. With the huge amount of information input and potential processing available in sensor networks, provenance is crucial for understanding the creation, manipulation and quality of data and processes. Thus maintaining provenance in a sensor network has substantial advantages. In our paper, we will concentrate on showing how provenance improves the outcome of a multi-modal sensor network with fusion. To make the ideas more concrete and to show what maintaining provenance provides, we will use a sensor network composed of binary proximity sensors and cameras to monitor intrusions as an example. Provenance provides improvements in many aspects such as sensing energy consumption, network lifetime, result accuracy, node failure rate. We will illustrate the improvements in accuracy of the position of the intruder in a target localization network by simulations. © 2012 SPIE.

关键词： sensor data fusion

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Lost in the Deep? Performance Evaluation of Dead Reckoning Techniques in Underwater Environments

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2023年第2期7卷 1-27页

作者： Radeta, Marko Rodrigues, Claudio Silva, Francisco Abreu, Pedro Pestana, Joao Nguyen, Ngoc Thi Zuniga, Agustin Flores, Huber Nurmi, Petteri Univ Madeira Fac Exact Sci & Engn Wave Labs Funchal Portugal Agencia Reg Desenvolvimento Invest Tecnol Inovaca ARNET Aquat Res Network MARE Marine & Environm Sci Ctr Funchal Portugal Univ Belgrade Dept Astron Fac Math Funchal Portugal Univ Madeira Wave Labs MARE ARDITIAR NET Funchal Portugal Univ Madeira Wave Labs MARE ARNETARDITI Funchal Portugal Univ Helsinki Dept Comp Sci Helsinki Finland Univ Tartu Inst Comp Sci Tartu Estonia

Computing research is increasingly addressing underwater environments and examining how computing can support diving and other activities. Unlike on land, where well-established positioning methods are widely available, underwater environments lack a common positioning mechanism, which is a prerequisite for many applications. Dead reckoning, the use of angle and distance estimates to track position changes from a known point of origin, is a promising candidate for underwater positioning as it does not rely on wireless signals (which decay rapidly in underwater environments) and as there is a wide range of literature and algorithms freely available. Yet, currently it is unclear whether the existing techniques can be adopted in underwater environments or whether the differences in medium and environment affect the performance of the dead reckoning techniques. We contribute by evaluating and systematically analyzing the performance and trade-offs associated with dead reckoning techniques in underwater environments. We present AEOLUS, a prototype unit comprising of a low-cost microcontroller and inertial measurement unit, to perform experiments on the ground and in underwater environments to assess how well the performance of different techniques translates from ground-based use cases to underwater environments. We benchmark 15 different algorithms and compare their performance in such environments to identify common patterns and dissimilarities, and identify root causes for these differences. The results show that displacement and turn errors can be estimated to within 5% error but that the best performing methods vary between land and underwater environments. We also show that the performance depends on the shape of the motion patterns with some algorithms performing better for hard turns whereas others perform better for gradual, more continuous turns.

关键词： sensor fusion Dead Reckoning Water Sensing Internet of Things AHRS Orientation Estimation Position Estimation Location Estimation IMU Underwater Positioning Review

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A Source-Attractor Approach to Network Detection of Radiation Sources

A Source-Attractor Approach to Network Detection of Radiatio...

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IEEE International Conference on Multisensor fusion and Integration for Intelligent Systems (MFI)

作者： Wu, Chase Q. Berry, Mark L. Grieme, Kayla M. Sen, Satyabrata Rao, Nageswara S. V. Brooks, Richard R. Cordone, Guthrie New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN 37831 USA Clemson Univ Dept Elect & Comp Engn Clemson SC 29634 USA

ISBN: (纸本)9781467397087

Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a "magnet"-like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not require an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localization-based methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office's (DNDO) Intelligence Radiation sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.

关键词： Radiation detection object localization sensor networks

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End-to-End Multimodal sensor Dataset Collection Framework for Autonomous Vehicles

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sensorS 2023年第15期23卷 6783-6783页

作者： Gu, Junyi Lind, Artjom Chhetri, Tek Raj Bellone, Mauro Sell, Raivo Tallinn Univ Technol Tallinn Dept Mech & Ind Engn EE-12616 Tallinn Estonia Univ Tartu Inst Comp Sci Intelligent Transportat Syst Lab EE-51009 Tartu Estonia Univ Innsbruck Semant Technol Inst STI Innsbruck Dept Comp Sci A-6020 Innsbruck Austria Ctr Artificial Intelligence AI Res Nepal Sundarharaincha 56604 Nepal Tallinn Univ Technol FinEst Ctr Smart Cities EE-19086 Tallinn Estonia

Autonomous driving vehicles rely on sensors for the robust perception of their surroundings. Such vehicles are equipped with multiple perceptive sensors with a high level of redundancy to ensure safety and reliability in any driving condition. However, multi-sensor, such as camera, LiDAR, and radar systems raise requirements related to sensor calibration and synchronization, which are the fundamental blocks of any autonomous system. On the other hand, sensor fusion and integration have become important aspects of autonomous driving research and directly determine the efficiency and accuracy of advanced functions such as object detection and path planning. Classical model-based estimation and data-driven models are two mainstream approaches to achieving such integration. Most recent research is shifting to the latter, showing high robustness in real-world applications but requiring large quantities of data to be collected, synchronized, and properly categorized. However, there are two major research gaps in existing works: (i) they lack fusion (and synchronization) of multi-sensors, camera, LiDAR and radar;and (ii) generic scalable, and user-friendly end-to-end implementation. To generalize the implementation of the multi-sensor perceptive system, we introduce an end-to-end generic sensor dataset collection framework that includes both hardware deploying solutions and sensor fusion algorithms. The framework prototype integrates a diverse set of sensors, such as camera, LiDAR, and radar. Furthermore, we present a universal toolbox to calibrate and synchronize three types of sensors based on their characteristics. The framework also includes the fusion algorithms, which utilize the merits of three sensors, namely, camera, LiDAR, and radar, and fuse their sensory information in a manner that is helpful for object detection and tracking research. The generality of this framework makes it applicable in any robotic or autonomous applications and suitable for quick and larg

关键词： multimodal sensors autonomous driving dataset collection framework sensor calibration and synchronization sensor fusion

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Field Experiments with an Automated Utility Platform for Transportation and Work Processes

Field Experiments with an Automated Utility Platform for Tra...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Edlinger, Raimund Dumberger, Stefan Froschauer, Roman Pointner, Wolfgang Zeilinger, Marcel Nuechter, Andreas Univ Appl Sci Upper Austria Smart Automat & Robot Wels Austria AIT Austrian Inst Technol Assist & Autonomous Syst Vienna Austria Julius Maximilians Univ Wurzburg Informat Robot & Telemat 7 Wurzburg Germany

ISBN: (纸本)9781665482172

The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features;(ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.

关键词： Localization Mapping and Navigation applications of Autonomous Intelligent Robots Autonomous Robotic Systems Robotic Simulation sensors and sensor Integration

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A MULTI-sensor APPROACH TO SURVEY COMPLEX architectures SUPPORTED BY MULTI-CAMERA PHOTOGRAMMETRY 29

A MULTI-SENSOR APPROACH TO SURVEY COMPLEX ARCHITECTURES SUPP...

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29th CIPA Symposium on Documenting, Understanding, Preserving Cultural Heritage - Humanities and Digital Technologies for Shaping the Future

作者： Perfetti, L. Spettu, F. Achille, C. Fassi, F. Navillod, C. Cerutti, C. Politecn Milan Dept Architecture Built Environm & Construct Engn Milan Italy Univ Brescia Dept Civil Engn Architecture Terr Environm & Math Brescia Italy cNarc Fraz Avout 6 Aosta Italy

Point clouds are nowadays a standard format of three-dimensional data. Various survey techniques are available, differing in characteristics, mode of use, and target applications, nevertheless producing point clouds that are similar, comparable, and combinable. According to recent literature, combining data from multiple sensors is an established practice for large surveying projects, particularly in Cultural Heritage, where the geometric complexity of buildings encourages the employment of many sensors. This paper presents a multi-sensor approach to surveying complex architectural spaces. The case study is the Cathedral of Aosta (AO) in Italy, which is interested in a conservation project that requires investigating the two bell towers of the cathedral. The survey aimed to produce a point cloud of 5 mm resolution and 1-2 cm accuracy compatible with the 1:50 scale of representation. The following survey techniques were employed: (i) laser scanning, (ii) terrestrial photogrammetry, (iii) UAV photogrammetry, and (iv) multi-camera fisheye photogrammetry. The distinctive feature of our approach lies in the multi-camera survey, conducted using a prototype composed of five fisheye cameras. The paper describes the data acquisition phase conducted with the different techniques, the mutual verification of the data performed by cross-sections check, the segmentation, and the final assembly of the various portions until a complete point cloud with homogeneous characteristics is obtained. All the data were then collected in a web platform (FlyVast) enriched with data and info made available to the professional to plan future interventions.

关键词： Cultural heritage Data fusion Point cloud Photogrammetry Laser scanning UAV Multicamera

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