Showing 4 open source projects for "raspberry 2"

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  • 1
    Snap7

    Snap7

    32/64 bit multi-platform Ethernet S7 PLC communication suite

    Snap7, through three specialized components: Client and the inedited Server and Partner, allows you to definitively integrate your PC based systems into a PLC automation chain. Designed to transfer large amounts of hi-speed data in industrial facilities, it scales easily, down to small Linux Arm boards such as Raspberry PI. Hi level object oriented wrappers are provided, currently C/C++, .NET/Mono, Pascal, LabVIEW, Python with many source code examples. Very easy to use, a full...
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    Downloads: 989 This Week
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  • 2

    json-scada

    A portable SCADA/IoT platform centered on the MongoDB database server.

    Standard IT tools applied to SCADA/IoT (MongoDB, PostgreSQL/TimescaleDB,Node.js, C#, Golang, Grafana, etc.). MongoDB as the real-time core database, persistence layer, config store, SOE historian. Portability and interoperability over Linux, Windows, x86/64, ARM. Horizontal scalability, from a single computer to big clusters (MongoDB-sharding), Bare Metal, Docker containers, VM, cloud, or hybrid deployments. Unlimited tags, servers, and users. HTML5 Web interface. UTF-8/I18N. Protocols:...
    Downloads: 3 This Week
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  • 3
    Agena

    Agena

    Agena is an interpreted procedural programming language.

    Agena is an easy-to-learn procedural programming language designed for science, scripting, and many other applications. Binaries are available for Windows, Linux, Solaris, OS/2, Mac OS X, Raspberry Pi and DOS.
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    Downloads: 138 This Week
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  • 4
    LaMa

    LaMa

    LaMa - A Localization and Mapping library

    LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. We provide a fast scan-matching approach to mobile robot localization supported by a continuous likelihood field. ...
    Downloads: 0 This Week
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