It was good to see some returning members and meet some new members at the Junior Robotics Kickoff meeting on Monday. We have a lot of new challenges ahead of us this fall, so I’d like to get a strong start to this semester.
Many of you know that we currently use two different languages or environments for programming the big robot. We use Python with OpenCV to code our vision system on the nVidia Jetson platform, and we use LabVIEW for the main robot and dashboard programming. This fall, we will also be investigating several different ways of programming an Android based controller for our First Tech Challenge (FTC) team. None of the FTC options are Python or LabVIEW, so it will be a great opportunity to learn something new.
This summer, we posted some mild programming challenges on the team website. The primary goal of the challenges was to develop problem-solving skills. Problem solving is what is really underneath all programming and engineering. The secondary goal was to get more exposure to working with either LabVIEW or Python. I encourage all new and existing team members to look at, and attempt these challenges, as it will really help in learning programming languages that may be new to you.
The lowest-cost of entry option for the programming contests is using Python, as it is free and works on Windows, macOS, and Linux. If your computer doesn’t already have it installed (this is mostly a Windows problem), you can download the appropriate package from http://python.org. We are currently using version 2.7.x.
I am putting together a virtual machine image for vision programming. This image will closely replicate the working environment on the Jetson, so that more work can be done without having to physically have access to the Jetson hardware. More details will be shared on Thursday night. If you want to get a head start, you can download and install Oracle’s VirtualBox software (free), which is available for Windows and macOS. It is available at https://www.virtualbox.org. I anticipate that the virtual machine image will take around 10 GB of space, when it is completed.
Hope to see you Thursday!