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Robotics Developer Studio

Robotics Developer Studio
<a id="b7777d05-f9ee-bedd-c9b9-9572b26f11d1" target="_self" class="mscom-link download-button dl" href="confirmation.aspx?id=29081" bi:track="false"><span class="loc" locid="46b21a80-a483-c4a8-33c6-eb40c48bcd9d" srcid="46b21a80-a483-c4a8-33c6-eb40c48bcd9d">Download</span></a> Microsoft® Robotics Developer Studio 4 is a freely available .NET-based programming environment for building robotics applications. It can be used by both professional and non-professional developers as well as hobbyists. DetailsMicrosoft Robotics Developer Studio 4.exe Microsoft® Robotics Developer Studio 4 enables hobbyists and professional or non-professional developers to create robotics applications targeting a wide range of scenarios. Related:  Flow Based Programming

Streamlining the Creation of Custom Visualization Applications Data exploration through visualization is an effective means to understand and obtain insights from large collections of data. Not surprisingly, visualization has become a mature area with an established research agenda [21], and several systems have been developed that support the creation of complex visualizations [6], [12], [14], [20], [22], [32], [35]. But even using systems that have sophisticated visual programming interfaces, such as AVS, DX, SCIRun, and VisTrails, the path from the raw data to insightful visualizations is laborious and error-prone. And this has hampered a wider adoption of visualization techniques. Fig. 1. View All | Next Visual programming interfaces expose computational components as modules and allow the creation of complex visualization pipelines which combine these modules in a dataflow, where connections between modules express the flow of data through the pipeline [16]. Our Approach. Outline. Dataflows. Definition 1. Definition 2. 3.1 Pipeline Operations

Sariel.pl Rapid Visualization Development based on Visual Programming :: Institut für Computergraphik und Algorithmen - Arbeitsgruppe für Computergraphik Information Publication Type: Master Thesis First Supervisor: Martin Haidacher Keywords: Rapid Development, Dataflow Programming, Visual Programming, Visualization Abstract Over the years, many visualization tools and applications were developed for specific fields of science or business. Staying in the alcove of their field, these are highly suited and optimized for visualizing specific data, with the drawback of not being flexible enough to extend or alter these visualizations for other purposes. Often, customers of such visualization packages cannot extend them, to fit their needs, especially if the software is closed source. The goal of this thesis is to develop a dataflow visual programming language (DFVPL) and a visual editor for the rapid development of visualizations. This programming language and its editor run platform independently to reach a high number of potential programmers, respectively users, to develop visualizations, since they are not bound to a specific platform.

MitchTech | Android, Linux, and embedded development Live Coding: Automated Artistic "Performances" Using Linux's Kernel We’ve been hearing the warnings from cautious futurists for years—one day, computer automation and robots would become so advanced as to be able to produce anything, perhaps even art. Though the creative and social implications of this forecast have been explored by generative artists for years now, we have yet to see any fully automated programs emerge wherein the computer creates art completely independently of the artist (even in generative art, humans still outline the parameters for the ensuing visuals through code). What if the computer programmed itself using that same generative technique, moving the possibilities of “computer-generated art” ever further down the rabbit hole of automation? The second project is a machine designed to self-program itself, leaving the human factor by the wayside almost completely. It's a machine's self-analysis that observes their status through the analysis of what goes into the kernel—the core of the machine’s operating system—in real-time.

Feature: Top 10 LEGO Mindstorms Creations You've seen the strangest LEGO creations, now check out the top ten LEGO Mindstorms creations. Whether it be a Pirates movie theater, pinball machine, or even a robotic toilet flusher, you'll find them here. Continue reading to view them all. 10. LEGO Printer YouTube user "horseattack" has uploaded a video of a functional LEGO printer that he built, connected to an Apple Mac. [Source] 9. A LEGO master wanted to create something that could actually be used, so a pinball machine came to mind. [Source] 8. If you're a LEGO minifig, you don't need frills like an HDTV projector or Blu-ray disc player. [Sources 1 | 2] 7. Here's a first: a pancake-making robot created using "LEGO Mindstorms, LEGO bricks and two ketchup bottles." [Source] 6. Here's a first: a fully-functional digital clock made with LEGO Mindstorms. [Sources 1 | 2] 5. Let's face it, not everyone is a master at Sudoku, but solving the puzzles just got a lot easier...if you've got one of these LEGO Mindstorms robots that is. 4. 3. 2.

Patch Schematics – The Aesthetics of Constraint / Best Practices / guest post by Paul Prudence (@MrPrudence) Visual programming languages, languages that create programs by the manipulation of graphical elements, as opposed to specifying lines of text, have seen an increased popularity in recent years both in audio and video synthesis. Some of the more well-known environments, ones that are regularly used for projects that are featured on CAN, include VVVV (real-time motion graphics and physical IO) MAX/MSP (real-time music and multimedia), Pure Data (ostensibly an open source equivalent of MAX/MSP) and Quartz Composer (video synthesis for MAC). Visual programming owes its many of its conventions for the representation of information and programs from Flowcharts – a lesser used term for these kinds of environments is Data-flow Programming. VPL’s date back to the late 60′s. A good example is the GraIL system (GRaphical Input Language) a flowchart language entered on a graphics tablet developed by the Rand Corporation in 1969. DMX-LED Patches – Kalle Karlen Parhelia subpatch group – Paul Prudence

Designing Lego Mindstorms NXT sensors - Stew’s Spot I bought a Lego Mindstorms kit last month to mess with, I’ve got some ideas for robot localisation that I want to try out. Anyway, the kit comes with a sonar range finder but I wanted a little more accuracy and smaller detection area. I’ve got a bunch of Sharp rangefinders from another project and they would work perfectly for what I wanted. A couple of companies sell after market sensors for the NXT, Mindsensors and HiTechnic but it’s much more fun to design and build your own. For a little background on how the Sharp sensors work, Acroname Robotics has a good article on them. I based the design on the following basic components. NXT Protocol NXT Connector (wikipedia) The NXT communicates with intelligent sensors via either a I2C or RS-485 bus, I’m using I2C for the rangefinder. System design, Schematics Click for PDF Overall a very simple design, there are a few aspects that I’ll touch on. The PCBs where manufactured by Betalayout PCB-Pool. Firmware The firmware is very simple. Calibration

The History of Programming Languages For 50 years, computer programmers have been writing code. New technologies continue to emerge, develop, and mature at a rapid pace. Now there are more than 2,500 documented programming languages! O'Reilly has produced a poster called History of Programming Languages (PDF: 701K), which plots over 50 programming languages on a multi-layered, color-coded timeline. How It Started We first saw the "History of Programming Languages" diagram, created by Éric Lévénez, while visiting our French office. About the O'Reilly Poster "Cool" is generally the first thing we heard from people who reviewed our poster. Getting Your Copy The poster is available online in PDF format (701k). Special Thanks Thanks to all who reviewed and commented on this poster along the way, including Éric Lévénez, Mark Brokering, Mark Stone, Daniel Steinberg, David Flanagan, Ian Darwin, Tim O'Reilly, Mike Hendrickson, Laurie Petrycki, Geoff Collyer, and Mark Brader.

R. J. McNamara Call graphs in Python | EJRH As a guide to program structure, and hopefully an aid to refactoring. It’s depressing to look at previous creations and realise how defective they are. This situation is something that programmers — perhaps more than any other group — routinely find themselves embarrassed by. In my case, I’ve returned to work on a work project dating from 2008. Gathering and merging config from the command line, a file, and a remote DBDownloading input from FTP serversMapping some data using remote DB tablesPutting output on queuesAutomatically retrying certain steps according to the configSending status emails The new work is to support a new type of input; the only real changes are in the input parser. The thing needs drastic refactoring. The immediate problem is that there’s no dependency injection. But I haven’t worked on it for 3 years. Searching for “refactoring python”, I found that others have had the same idea about refactoring using the call graph is a guide. It’s pretty cool. Like this:

Introduction to Houdini's Node Based Workflow Download Video - 49MB [16 Min.]Download Torrent Houdini is best known for its node-based workflow which makes it easy to step back and make changes. Everything you do in Houdini is recorded into nodes that are connected into networks that provide a history of your decisions that can be revised, rewired and shared with colleagues. While many applications create construction history stacks or build complex dependency graphs, they often offer only limited control. These systems either define a linear history or they use intricate parameter-based connections that must be managed via scripting. In Houdini, nodes are organized into nested hierarchies that are easy to manage and because connections are generalized, it is easy to swap out, rewire and even branch off to explore new ideas. The most important thing this video shows is that the ability to work with these nodes is interactive and friendly and can be easily accomplished by artists.

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