Getting Started with NVidia Jetson Nano via JetBot

As part of the effort to explore NVidia Jetson Nano, and part of its AI Specialist course (after finishing Fundamentals of AI in Nvidia Deep Learning Institute), I started buliding a JetBot.

JetBots are well documented and relatively easy to build provdied you have the right parts. There is also a bill of materials to make purchasing simpler.

The chassis was 3D printed according to the full DIY instructions (did not use a kit).

The camera used in this picture is actually from a Rasp Pi infrared camera I bought years ago. Turns out I could remove the lens and apply to another camera I bought for this project (IMX290-160FOV). It turns out that the 70 degree FOV on the lens was really just not wide enough to see what is going on. The 160-degree FOV was perfect and seems to help the bot see around itself.

This post is part of a series on learning about Internet of Things. These posts are mainly a learning tool for me – taking notes, jotting down ideas, and tracking progress. This means they might be unrelated to radiology or healthcare. They also might contain works-in-progress or inaccuracies.
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Howard Chen
Vice Chair for Artificial Intelligence at Cleveland Clinic Diagnostics Institute
Howard is passionate about making diagnostic tests more accurate, expedient, and affordable through disciplined implementation of advanced technology. He previously served as Chief Informatics Officer for Imaging, where he led teams deploying and unifying radiology applications and AI in a multi-state, multi-hospital environment. Blog opinions are his own and in no way reflect those of the employer.

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