2,162 research outputs found

    Safe, Remote-Access Swarm Robotics Research on the Robotarium

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    This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

    Robotic ubiquitous cognitive ecology for smart homes

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    Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

    A Nomadic Testbed for Teaching Computer Architecture

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    A nomadic laboratory or testbed, based on Raspberry Pi 3 computers and Arduino microcontrollers, has been developed in order to teach subjects related to computer architecture. The testbed can be transported to the classroom. Students can access it through the available network, which can be a wireless LAN, wired LAN o a custom network. The student can access without constraints to the platforms, therefore there are a wide range of possible experiments. This laboratory was used during 2017 for practical works in the course Introduction to Technology, and during 2018 in the course Computers Architecture at Universidad Nacional of Cuyo. Some of the experiments that are been carried out by students are: to explore and analyse the architecture of the computers through Linux commands, write and run programs on different programing languages, input and output operations through memory mapped addressing and isolated addressing, write interrupt service routines in order to service interrupts, multithreading programing, explore memory maps, CPU features, etc. This paper describes the testbed architecture, experiments performed by students in the mentioned subjects, present the students feedback, and describes the possible methods in order to integrate it to a remote laboratory.XVII Workshop Tecnología Informática Aplicada en Educación (WTIAE)Red de Universidades con Carreras en Informática (RedUNCI

    A Nomadic Testbed for Teaching Computer Architecture

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    A nomadic laboratory or testbed, based on Raspberry Pi 3 computers and Arduino microcontrollers, has been developed in order to teach subjects related to computer architecture. The testbed can be transported to the classroom. Students can access it through the available network, which can be a wireless LAN, wired LAN o a custom network. The student can access without constraints to the platforms, therefore there are a wide range of possible experiments. This laboratory was used during 2017 for practical works in the course Introduction to Technology, and during 2018 in the course Computers Architecture at Universidad Nacional of Cuyo. Some of the experiments that are been carried out by students are: to explore and analyse the architecture of the computers through Linux commands, write and run programs on different programing languages, input and output operations through memory mapped addressing and isolated addressing, write interrupt service routines in order to service interrupts, multithreading programing, explore memory maps, CPU features, etc. This paper describes the testbed architecture, experiments performed by students in the mentioned subjects, present the students feedback, and describes the possible methods in order to integrate it to a remote laboratory.XVII Workshop Tecnología Informática Aplicada en Educación (WTIAE)Red de Universidades con Carreras en Informática (RedUNCI

    Using SensLAB as a First Class Scienti c Tool for Large Scale Wireless Sensor Network Experiments

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    International audienceThis paper presents a description of SensLAB(Very Large Scale Open Wireless Sensor Network Testbed) that has been developed and deployed in order to allow the evaluation through experimentations of scalable wireless sensor network protocols and applications. SensLAB's main and most important goal is to o er an accurate open access multiusers scienti c tool to support the design, the development tuning, and the experimentation of real large-scale sensor network applications. The SensLAB testbed is composed of 1024 nodes over 4 sites. Each site hosts 256 sensor nodes with speci c characteristics in order to o er a wide spectrum of possibilities and heterogeneity. Within a given site, each one of the 256 nodes is able both to communicate via its radio interface to its neighbors and to be con gured as a sink node to exchange data with any other "sink node". The hardware and software architectures that allow to reserve, con gure, deploy rmwares and gather experimental data and monitoring information are described. We also present demonstration examples to illustrate the use of the SensLAB testbed and encourage researchers to test and benchmark their applications/protocols on a large scale WSN testbed

    Data-driven design of intelligent wireless networks: an overview and tutorial

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    Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves

    LTE Spectrum Sharing Research Testbed: Integrated Hardware, Software, Network and Data

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    This paper presents Virginia Tech's wireless testbed supporting research on long-term evolution (LTE) signaling and radio frequency (RF) spectrum coexistence. LTE is continuously refined and new features released. As the communications contexts for LTE expand, new research problems arise and include operation in harsh RF signaling environments and coexistence with other radios. Our testbed provides an integrated research tool for investigating these and other research problems; it allows analyzing the severity of the problem, designing and rapidly prototyping solutions, and assessing them with standard-compliant equipment and test procedures. The modular testbed integrates general-purpose software-defined radio hardware, LTE-specific test equipment, RF components, free open-source and commercial LTE software, a configurable RF network and recorded radar waveform samples. It supports RF channel emulated and over-the-air radiated modes. The testbed can be remotely accessed and configured. An RF switching network allows for designing many different experiments that can involve a variety of real and virtual radios with support for multiple-input multiple-output (MIMO) antenna operation. We present the testbed, the research it has enabled and some valuable lessons that we learned and that may help designing, developing, and operating future wireless testbeds.Comment: In Proceeding of the 10th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization (WiNTECH), Snowbird, Utah, October 201
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