13,586 research outputs found

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    TinyML: Tools, Applications, Challenges, and Future Research Directions

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    In recent years, Artificial Intelligence (AI) and Machine learning (ML) have gained significant interest from both, industry and academia. Notably, conventional ML techniques require enormous amounts of power to meet the desired accuracy, which has limited their use mainly to high-capability devices such as network nodes. However, with many advancements in technologies such as the Internet of Things (IoT) and edge computing, it is desirable to incorporate ML techniques into resource-constrained embedded devices for distributed and ubiquitous intelligence. This has motivated the emergence of the TinyML paradigm which is an embedded ML technique that enables ML applications on multiple cheap, resource- and power-constrained devices. However, during this transition towards appropriate implementation of the TinyML technology, multiple challenges such as processing capacity optimization, improved reliability, and maintenance of learning models' accuracy require timely solutions. In this article, various avenues available for TinyML implementation are reviewed. Firstly, a background of TinyML is provided, followed by detailed discussions on various tools supporting TinyML. Then, state-of-art applications of TinyML using advanced technologies are detailed. Lastly, various research challenges and future directions are identified.Comment: 12 pags, 3 tables, 4 figure

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Compliant aerial manipulation.

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    The aerial manipulation is a research field which proposes the integration of robotic manipulators in aerial platforms, typically multirotors – widely known as “drones” – or autonomous helicopters. The development of this technology is motivated by the convenience to reduce the time, cost and risk associated to the execution of certain operations or tasks in high altitude areas or difficult access workspaces. Some illustrative application examples are the detection and insulation of leaks in pipe structures in chemical plants, repairing the corrosion in the blades of wind turbines, the maintenance of power lines, or the installation and retrieval of sensor devices in polluted areas. Although nowadays it is possible to find a wide variety of commercial multirotor platforms with payloads from a few gramps up to several kilograms, and flight times around thirty minutes, the development of an aerial manipulator is still a technological challenge due to the strong requirements relative to the design of the manipulator in terms of very low weight, low inertia, dexterity, mechanical robustness and control. The main contribution of this thesis is the design, development and experimental validation of several prototypes of lightweight (<2 kg) and compliant manipulators to be integrated in multirotor platforms, including human-size dual arm systems, compliant joint arms equipped with human-like finger modules for grasping, and long reach aerial manipulators. Since it is expected that the aerial manipulator is capable to execute inspection and maintenance tasks in a similar way a human operator would do, this thesis proposes a bioinspired design approach, trying to replicate the human arm in terms of size, kinematics, mass distribution, and compliance. This last feature is actually one of the key concepts developed and exploited in this work. Introducing a flexible element such as springs or elastomers between the servos and the links extends the capabilities of the manipulator, allowing the estimation and control of the torque/force, the detection of impacts and overloads, or the localization of obstacles by contact. It also improves safety and efficiency of the manipulator, especially during the operation on flight or in grabbing situations, where the impacts and contact forces may damage the manipulator or destabilize the aerial platform. Unlike most industrial manipulators, where force-torque control is possible at control rates above 1 kHz, the servo actuators typically employed in the development of aerial manipulators present important technological limitations: no torque feedback nor control, only position (and in some models, speed) references, low update rates (<100 Hz), and communication delays. However, these devices are still the best solution due to their high torque to weight ratio, low cost, compact design, and easy assembly and integration. In order to cope with these limitations, the compliant joint arms presented here estimate and control the wrenches from the deflection of the spring-lever transmission mechanism introduced in the joints, measured at joint level with encoders or potentiometers, or in the Cartesian space employing vision sensors. Note that in the developed prototypes, the maximum joint deflection is around 25 degrees, which corresponds to a deviation in the position of the end effector around 20 cm for a human-size arm. The capabilities and functionalities of the manipulators have been evaluated in fixed base test-bench firstly, and then in outdoor flight tests, integrating the arms in different commercial hexarotor platforms. Frequency characterization, position/force/impedance control, bimanual grasping, arm teleoperation, payload mass estimation, or contact-based obstacle localization are some of the experiments presented in this thesis that validate the developed prototypes.La manipulación aérea es un campo de investigación que propone la integración de manipuladores robóticos in plataformas aéreas, típicamente multirotores – comúnmente conocidos como “drones” – o helicópteros autónomos. El desarrollo de esta tecnología está motivada por la conveniencia de reducir el tiempo, coste y riesgo asociado a la ejecución de ciertas operaciones o tareas en áreas de gran altura o espacios de trabajo de difícil acceso. Algunos ejemplos ilustrativos de aplicaciones son la detección y aislamiento de fugas en estructura de tuberías en plantas químicas, la reparación de la corrosión en las palas de aerogeneradores, el mantenimiento de líneas eléctricas, o la instalación y recuperación de sensores en zonas contaminadas. Aunque hoy en día es posible encontrar una amplia variedad de plataformas multirotor comerciales con cargas de pago desde unos pocos gramos hasta varios kilogramos, y tiempo de vuelo entorno a treinta minutos, el desarrollo de los manipuladores aéreos es todavía un desafío tecnológico debido a los exigentes requisitos relativos al diseño del manipulador en términos de muy bajo peso, baja inercia, destreza, robustez mecánica y control. La contribución principal de esta tesis es el diseño, desarrollo y validación experimental de varios prototipos de manipuladores de bajo peso (<2 kg) con capacidad de acomodación (“compliant”) para su integración en plataformas aéreas multirotor, incluyendo sistemas bi-brazo de tamaño humano, brazos robóticos de articulaciones flexibles con dedos antropomórficos para agarre, y manipuladores aéreos de largo alcance. Puesto que se prevé que el manipulador aéreo sea capaz de ejecutar tareas de inspección y mantenimiento de forma similar a como lo haría un operador humano, esta tesis propone un enfoque de diseño bio-inspirado, tratando de replicar el brazo humano en cuanto a tamaño, cinemática, distribución de masas y flexibilidad. Esta característica es de hecho uno de los conceptos clave desarrollados y utilizados en este trabajo. Al introducir un elemento elástico como los muelles o elastómeros entre el los actuadores y los enlaces se aumenta las capacidades del manipulador, permitiendo la estimación y control de las fuerzas y pares, la detección de impactos y sobrecargas, o la localización de obstáculos por contacto. Además mejora la seguridad y eficiencia del manipulador, especialmente durante las operaciones en vuelo, donde los impactos y fuerzas de contacto pueden dañar el manipulador o desestabilizar la plataforma aérea. A diferencia de la mayoría de manipuladores industriales, donde el control de fuerzas y pares es posible a tasas por encima de 1 kHz, los servo motores típicamente utilizados en el desarrollo de manipuladores aéreos presentan importantes limitaciones tecnológicas: no hay realimentación ni control de torque, sólo admiten referencias de posición (o bien de velocidad), y presentan retrasos de comunicación. Sin embargo, estos dispositivos son todavía la mejor solución debido al alto ratio de torque a peso, por su bajo peso, diseño compacto y facilidad de ensamblado e integración. Para suplir estas limitaciones, los brazos robóticos flexibles presentados aquí permiten estimar y controlar las fuerzas a partir de la deflexión del mecanismo de muelle-palanca introducido en las articulaciones, medida a nivel articular mediante potenciómetros o codificadores, o en espacio Cartesiano mediante sensores de visión. Tómese como referencia que en los prototipos desarrollados la máxima deflexión articular es de unos 25 grados, lo que corresponde a una desviación de posición en torno a 20 cm en el efector final para un brazo de tamaño humano. Las capacidades y funcionalidades de estos manipuladores se han evaluado en base fija primero, y luego en vuelos en exteriores, integrando los brazos en diferentes plataformas hexartor comerciales. Caracterización frecuencial, control de posición/fuerza/impedancia, agarre bimanual, teleoperación de brazos, estimación de carga, o la localización de obstáculos mediante contacto son algunos de los experimentos presentados en esta tesis para validar los prototipos desarrollados por el auto

    2020 NASA Technology Taxonomy

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    This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

    Ono: an open platform for social robotics

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    In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform
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