582 research outputs found

    Land & Localize: An Infrastructure-free and Scalable Nano-Drones Swarm with UWB-based Localization

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    Relative localization is a crucial functional block of any robotic swarm. We address it in a fleet of nano-drones characterized by a 10 cm-scale form factor, which makes them highly versatile but also strictly limited in their onboard power envelope. State-of-the-Art solutions leverage Ultra-WideBand (UWB) technology, allowing distance range measurements between peer nano-drones and a stationary infrastructure of multiple UWB anchors. Therefore, we propose an UWB-based infrastructure-free nano-drones swarm, where part of the fleet acts as dynamic anchors, i.e., anchor-drones (ADs), capable of automatic deployment and landing. By varying the Ads' position constraint, we develop three alternative solutions with different trade-offs between flexibility and localization accuracy. In-field results, with four flying mission-drones (MDs), show a localization root mean square error (RMSE) spanning from 15.3 cm to 27.8 cm, at most. Scaling the number of MDs from 4 to 8, the RMSE marginally increases, i.e., less than 10 cm at most. The power consumption of the MDs' UWB module amounts to 342 mW. Ultimately, compared to a fixed-infrastructure commercial solution, our infrastructure-free system can be deployed anywhere and rapidly by taking 5.7 s to self-localize 4 ADs with a localization RMSE of up to 12.3% in the most challenging case with 8 MDs

    A Low-Cost Ultra-Wideband Test-Bed

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    This paper presents the design and implementation of a simple transceiver test-bed for implementing and testing algorithms for impulsive UWB applications. The platform has been developed using low-cost off-the-shelf components. We have conceived a simple modular architecture that was targeted to low power, short-range applications. The test-bed is discussed,commenting on the main design decisions and the benefits of the chosen architecture. Measurements of some blocks of the system are also presented.Fil: Altieri, Andrés Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; ArgentinaFil: Gámez, Pablo. Instituto Nacional de Tecnología Industrial; ArgentinaFil: Marchi, Edgardo Jose. Instituto Nacional de Tecnología Industrial; ArgentinaFil: Cervetto, Marcos. Instituto Nacional de Tecnología Industrial; ArgentinaFil: Bouza, Magadalena. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; ArgentinaFil: Galarza, Cecilia Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; ArgentinaXXXV Simpósio Brasileiro de Telecomunicações e Processamento de SinaisSan PedroBrasilSociedade Brasileira de Telecomunicaçõe

    Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

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    Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure

    Whitepaper on New Localization Methods for 5G Wireless Systems and the Internet-of-Things

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    Edge Artificial Intelligence for Real-Time Target Monitoring

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    The key enabling technology for the exponentially growing cellular communications sector is location-based services. The need for location-aware services has increased along with the number of wireless and mobile devices. Estimation problems, and particularly parameter estimation, have drawn a lot of interest because of its relevance and engineers' ongoing need for higher performance. As applications expanded, a lot of interest was generated in the accurate assessment of temporal and spatial properties. In the thesis, two different approaches to subject monitoring are thoroughly addressed. For military applications, medical tracking, industrial workers, and providing location-based services to the mobile user community, which is always growing, this kind of activity is crucial. In-depth consideration is given to the viability of applying the Angle of Arrival (AoA) and Receiver Signal Strength Indication (RSSI) localization algorithms in real-world situations. We presented two prospective systems, discussed them, and presented specific assessments and tests. These systems were put to the test in diverse contexts (e.g., indoor, outdoor, in water...). The findings showed the localization capability, but because of the low-cost antenna we employed, this method is only practical up to a distance of roughly 150 meters. Consequently, depending on the use-case, this method may or may not be advantageous. An estimation algorithm that enhances the performance of the AoA technique was implemented on an edge device. Another approach was also considered. Radar sensors have shown to be durable in inclement weather and bad lighting conditions. Frequency Modulated Continuous Wave (FMCW) radars are the most frequently employed among the several sorts of radar technologies for these kinds of applications. Actually, this is because they are low-cost and can simultaneously provide range and Doppler data. In comparison to pulse and Ultra Wide Band (UWB) radar sensors, they also need a lower sample rate and a lower peak to average ratio. The system employs a cutting-edge surveillance method based on widely available FMCW radar technology. The data processing approach is built on an ad hoc-chain of different blocks that transforms data, extract features, and make a classification decision before cancelling clutters and leakage using a frame subtraction technique, applying DL algorithms to Range-Doppler (RD) maps, and adding a peak to cluster assignment step before tracking targets. In conclusion, the FMCW radar and DL technique for the RD maps performed well together for indoor use-cases. The aforementioned tests used an edge device and Infineon Technologies' Position2Go FMCW radar tool-set

    Realization Limits of Impulse-Radio UWB Indoor Localization Systems

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    In this work, the realization limits of an impulse-based Ultra-Wideband (UWB) localization system for indoor applications have been thoroughly investigated and verified by measurements. The analysis spans from the position calculation algorithms, through hardware realization and modeling, up to the localization experiments conducted in realistic scenarios. The main focus was put on identification and characterization of limiting factors as well as developing methods to overcome them

    A Survey on Subsurface Signal Propagation

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    Wireless Underground Communication (WUC) is an emerging field that is being developed continuously. It provides secure mechanism of deploying nodes underground which shields them from any outside temperament or harsh weather conditions. This paper works towards introducing WUC and give a detail overview of WUC. It discusses system architecture of WUC along with the anatomy of the underground sensor motes deployed in WUC systems. It also compares Over-the-Air and Underground and highlights the major differences between the both type of channels. Since, UG communication is an evolving field, this paper also presents the evolution of the field along with the components and example UG wireless communication systems. Finally, the current research challenges of the system are presented for further improvement of the WUCs

    Improving domiciliary robotic services by integrating the ASTRO Robot in an AmI Infrastructure

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    This work describes the ECHORD Experiment ASTROMOBILE, a project aimed to design, develop and test a system for favourable independent living, improved quality of life and efficiency of care for senior citizens in domestic environments. The system, composed of a mobile robotic platform (called ASTRO) and an Ambient Intelligent Infrastructure that actively cooperated between them and with the end-user, was designed and implemented with a user-centred design approach, involving different stakeholders. The system was designed to deliver services to users, like drug delivery, stand support, reminding, info-entertainment. The design took advantages of the integration of robotic platforms with smart environments, to provide to users higher quality and localization based services. Senior end-users were involved in the experimentation of the system in the DomoCasa Living Lab and feedbacks were gathered for the technology assessment. Particularly, this paper demonstrates the general feasibility of the ASTROMOBILE system and thanks to users feedbacks its acceptability and usability
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