Processing the positioning information of visual objects detected by Pixy camera and received on Raspberry Pi via I2C, and using common design patterns in a C# program parsing robotics sensor data
Cool project with really thorough code documentation by Victor Dashevsky spotted over at codeproject:
Many of us when we first dive into robotics at some point have to pick our very first sensor to play with. Although I have not started with Pixy, for moderately experienced programmers, Pixy makes a reasonable first choice. It is crunching lots of visual info to deliver object positioning data to you in a compact format 50 times per second. Being able to track a visual object in your program with an investment of only $69 is pretty cool!
I completed this project over a year ago on Raspberry PI 2 and Visual Studio 2015 but these days you can use RPI 3 Model B+ and VS 2017. At the time of this writing, Pixy CMUcam5 that I used remains the latest version of the device.
For robotics enthusiasts new to Windows 10 IoT Core and C#, I’d like to add that the freely available development framework provided by Microsoft enables mastering the same technology as what numerous professional programmers use to build enterprise software and commercial web sites. Using VS.NET and applying Object Oriented Programming principles, you can build a large well organized system positioned for growth. Standard design patterns, NuGet packages, code libraries and ready-to-use solutions are available to us allowing to extend an experimental app way beyond its original scope. If you consider separation of concerns, segregation of logic within layers and loose coupling between them early in your design, you will be enjoying your growing project for years to come. This remains true whether building robotics apps professionally or as a hobby.
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Track Objects using Raspberry Pi & Pixy CMUcam5 Sensor with Windows 10 IoT Core | #piday #raspberrypi @Raspberry_Pi
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