160 research outputs found

    Enabling Runtime Self-Coordination of Reconfigurable Embedded Smart Cameras in Distributed Networks

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    Smart camera networks are real-time distributed embedded systems able to perform computer vision using multiple cameras. This new approach is a confluence of four major disciplines (computer vision, image sensors, embedded computing and sensor networks) and has been subject of intensive work in the past decades. The recent advances in computer vision and network communication, and the rapid growing in the field of high-performance computing, especially using reconfigurable devices, have enabled the design of more robust smart camera systems. Despite these advancements, the effectiveness of current networked vision systems (compared to their operating costs) is still disappointing; the main reason being the poor coordination among cameras entities at runtime and the lack of a clear formalism to dynamically capture and address the self-organization problem without relying on human intervention. In this dissertation, we investigate the use of a declarative-based modeling approach for capturing runtime self-coordination. We combine modeling approaches borrowed from logic programming, computer vision techniques, and high-performance computing for the design of an autonomous and cooperative smart camera. We propose a compact modeling approach based on Answer Set Programming for architecture synthesis of a system-on-reconfigurable-chip camera that is able to support the runtime cooperative work and collaboration with other camera nodes in a distributed network setup. Additionally, we propose a declarative approach for modeling runtime camera self-coordination for distributed object tracking in which moving targets are handed over in a distributed manner and recovered in case of node failure

    Contactless WiFi Sensing and Monitoring for Future Healthcare:Emerging Trends, Challenges and Opportunities

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    WiFi sensing has recently received significant interest from academics, industry, healthcare professionals and other caregivers (including family members) as a potential mechanism to monitor our aging population at distance, without deploying devices on users bodies. In particular, these methods have gained significant interest to efficiently detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems stems from its practical deployments in indoor settings and compliance from monitored persons, unlike other sensors such as wearables, camera-based, and acoustic-based solutions. This paper reviews state-of-the-art research on collecting and analysing channel state information, extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, untapped areas, and related trends.This work aims to provide an overarching view in understanding the technology and discusses its uses-cases from a perspective that considers hardware, advanced signal processing, and data acquisition

    New Approach of Indoor and Outdoor Localization Systems

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    Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

    Ultra Wideband

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    Ultra wideband (UWB) has advanced and merged as a technology, and many more people are aware of the potential for this exciting technology. The current UWB field is changing rapidly with new techniques and ideas where several issues are involved in developing the systems. Among UWB system design, the UWB RF transceiver and UWB antenna are the key components. Recently, a considerable amount of researches has been devoted to the development of the UWB RF transceiver and antenna for its enabling high data transmission rates and low power consumption. Our book attempts to present current and emerging trends in-research and development of UWB systems as well as future expectations

    Enabling technologies for distributed body sensor networks

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    Low Power Wireless Sensor Networks, Preventative Healthcare and Pervasive Systems are set to provide long-term continuous monitoring, diagnosis and care for patients in the next few years. Distributed forms of these networks are investigated from a holistic point of view. Individual components of these systems including: sensors, software and hardware implementations are investigated and analysed. Novel sensors are developed for low power capturing of Body Sensor Network (BSN) information to enable long term use. Software frameworks are designed to enable these technologies to run on low power nodes as well as enabling them to perform evaluation of their data before transmission into the network. An architecture is designed to enable task distribution to intensive processing from low power nodes. Two forms of distributed BSNs are also developed: a horizontal network and a vertical network. It is shown that using these two types of networks enables information and task distribution allowing low power sensing nodes to evaluate information before transmission. These systems have the opportunity to revolutionalise expensive acute episodic care systems of today, but are not currently being implemented or investigated to the extent that they could. The technological barriers to entry are addressed in this thesis with the investigation and evaluation of distributed body sensor networks. It is shown that horizontal networks can distribute information efficiently, while vertical networks can distribute processing efficiently

    AI and IoT Meet Mobile Machines

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    Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

    Advances in Intelligent Robotics and Collaborative Automation

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    This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:ā€¢ Robotsā€¢ Control and Intelligenceā€¢ Sensingā€¢ Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

    Toward Vision-based Control of Heavy-Duty and Long-Reach Robotic Manipulators

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    Heavy-duty mobile machines are an important part of the industry, and they are used for various work tasks in mining, construction, forestry, and agriculture. Many of these machines have heavy-duty, long-reach (HDLR) manipulators attached to them, which are used for work tasks such as drilling, lifting, and grabbing. A robotic manipulator, by deļ¬nition, is a device used for manipulating materials without direct physical contact by a human operator. HDLR manipulators diļ¬€er from manipulators of conventional industrial robots in the sense that they are subject to much larger kinematic and non-kinematic errors, which hinder the overall accuracy and repeatability of the robotā€™s tool center point (TCP). Kinematic errors result from modeling inaccuracies, while non-kinematic errors include structural ļ¬‚exibility and bending, thermal eļ¬€ects, backlash, and sensor resolution. Furthermore, conventional six degrees of freedom (DOF) industrial robots are more general-purpose systems, whereas HDLR manipulators are mostly designed for special (or single) purposes. HDLR manipulators are typically built as lightweight as possible while being able to handle signiļ¬cant load masses. Consequently, they have long reaches and high payload-to-own-weight ratios, which contribute to the increased errors compared to conventional industrial robots. For example, a joint angle measurement error of 0.5ā—¦ associated with a 5-m-long rigid link results in an error of approximately 4.4 cm at the end of the link, with further errors resulting from ļ¬‚exibility and other non-kinematic aspects. The target TCP positioning accuracy for HDLR manipulators is in the sub-centimeter range, which is very diļ¬ƒcult to achieve in practical systems. These challenges have somewhat delayed the automation of HDLR manipulators, while conventional industrial robots have long been commercially available. This is also attributed to the fact that machines with HDLR manipulators have much lower production volumes, and the work tasks are more non-repetitive in nature compared to conventional industrial robots in factories. Sensors are a key requirement in order to achieve automated operations and eventually full autonomy. For example, humans mostly rely on their visual perception in work tasks, while the collected information is processed in the brain. Much like humans, autonomous machines also require both sensing and intelligent processing of the collected sensor data. This dissertation investigates new visual sensing solutions for HDLR manipulators, which are striving toward increased automation levels in various work tasks. The focus is on visual perception and generic 6 DOF TCP pose estimation of HDLR manipulators in unknown (or unstructured) environments. Methods for increasing the robustness and reliability of visual perception systems are examined by exploiting sensor redundancy and data fusion. Vision-aided control using targetless, motion-based local calibration between an HDLR manipulator and a visual sensor is also proposed to improve the absolute positioning accuracy of the TCP despite the kinematic and non-kinematic errors present in the system. It is experimentally shown that a sub-centimeter TCP positioning accuracy was reliably achieved in the tested cases using a developed trajectory-matching-based method. Overall, this compendium thesis includes four publications and one unpublished manuscript related to these topics. Two main research problems, inspired by the industry, are considered and investigated in the presented publications. The outcome of this thesis provides insight into possible applications and beneļ¬ts of advanced visual perception systems for HDLR manipulators in dynamic, unstructured environments. The main contribution is related to achieving sub-centimeter TCP positioning accuracy for an HDLR manipulator using a low-cost camera. The numerous challenges and complexities related to HDLR manipulators and visual sensing are also highlighted and discussed

    Advances in Intelligent Robotics and Collaborative Automation

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    This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:ā€¢ Robotsā€¢ Control and Intelligenceā€¢ Sensingā€¢ Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area
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