AWS DeepRacer is the fastest way to get started with machine learning (ML). You can train reinforcement learning (RL) models by using a 1/18th scale autonomous vehicle in a cloud-based virtual simulator and compete for prizes and glory in the global AWS DeepRacer League. Today, we’re expanding AWS DeepRacer’s ability to provide fun, hands-on learning by open-sourcing the AWS DeepRacer device software.
Why open source
The AWS DeepRacer virtual and in-person leagues have been a hit, but now developers want to go beyond league racing with their car. Because the AWS DeepRacer is an Ubuntu-based computer on wheels powered by the Robot Operating System (ROS) we are able to open source the code, making it straightforward for a developer with basic Linux coding skills to prototype new and interesting uses for their car. Now that the AWS DeepRacer device software is openly available, anyone with the car and an idea can make new uses for their device a reality.
We’ve compiled 6 sample projects from the AWS DeepRacer team and members of the global AWS DeepRacer community to help you get started exploring the possibilities that open source provides. As developers share new projects using #deepracerproject, we will highlight our favorites on the AWS DeepRacer robotics projects page. Whether you’re mounting a Nerf cannon on the car with the DeepBlaster project, creating visualizations of your home or office with the Mapping project, or coming up with new ways of racing your friends and colleagues with the DeepDriver project, you can do all that and more with the open source code and sample projects. Documentation is available in GitHub and open for collaboration with thousands of community members in the AWS DeepRacer Slack channel. The only limit to what you can do with AWS DeepRacer is your imagination (and, well, the laws of physics).
Let the experiments begin
With the open-sourcing of the AWS DeepRacer device code, you can quickly and easily change the default behavior of your currently track-obsessed race car. Want to block other cars from overtaking it by deploying countermeasures? Want to deploy your own custom algorithm to make the car go faster from point A to B? You just need to dream it and code it. We can’t wait to see the ideas that you come up with, from new racing formats to new uses for AWS DeepRacer.
Starting today, you can choose from six projects (Follow the leader, Mapping, and Off Road created by AWS, and RoboCat, DeepBlaster, and DeepDriver created by the open source community) or create your own. You can get started with the Follow the Leader sample project, which trains the car to detect and follow an object. It’s the quickest project to build and run, and in the next section we’ll demonstrate how easy it is to modify the default t
Source - Continue Reading: https://aws.amazon.com/blogs/machine-learning/aws-deepracer-device-software-now-open-source/