Developers, start your engines
Developers of all skill levels can get hands on with machine learning through a cloud based 3D racing simulator, fully autonomous 1/18th scale race car driven by reinforcement learning, and global racing league.
In pole position to learn reinforcement learning
AWS DeepRacer gives you an interesting and fun way to get started with reinforcement learning (RL). RL is an advanced machine learning (ML) technique that takes a very different approach to training models than other machine learning methods. Its super power is that it learns very complex behaviors without requiring any labeled training data, and can make short term decisions while optimizing for a longer term goal.
Build models in Amazon SageMaker and train, test, and iterate quickly and easily on the track in the AWS DeepRacer 3D racing simulator.
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Experience the thrill of the race in the real-world when you deploy your reinforcement learning model onto AWS DeepRacer.
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Compete in the world’s first global, autonomous racing league, to race for prizes and glory and a chance to advance to the Championship Cup.
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Get started with machine learning quickly with hands-on tutorials that help you learn the basics of machine learning, start training reinforcement learning models and test them in an exciting, autonomous car racing experience.
Test these new found skills in the AWS DeepRacer 3D racing simulator. Experiment with multiple sensor inputs, the latest reinforcement learning algorithms, neural network configurations and simulation to-real domain transfer methods.
The AWS DeepRacer League provides an opportunity for you to compete for prizes and meet fellow machine learning enthusiasts, online and in person. Share ideas and insights on how to succeed and create your own private virtual race.
Compete in the AWS DeepRacer League
Once you have built your model, it’s time to race! The AWS DeepRacer League is the world’s first global autonomous racing league, open to anyone. Developers can compete from anywhere in the world for prizes, glory, and a chance to advance to the AWS DeepRacer Championship Cup Finals at re:Invent 2021!
Join the global AWS DeepRacer League. Compete in time trial races and take on new challenges such as head-to-head racing.
With community races you can host your own races to challenge your colleagues; or share publicly with ML enthusiasts around the globe.
AWS DeepRacer Enterprise events are the fastest way to get your company rolling on their machine learning journey.
With new AWS DeepRacer LIVE races anyone can set up a race in minutes and stream it live. Invite your friends and colleagues to submit their models to compete in real time with easy to use hosting tools for streaming your race in console and on Twitch.
The rubber meets the road
AWS DeepRacer is an autonomous 1/18th scale race car designed to test RL models by racing on a physical track. Using cameras to view the track and a reinforcement model to control throttle and steering, the car shows how a model trained in a simulated environment can be transferred to the real-world.
Introducing the AWS DeepRacer Evo
AWS DeepRacer Evo is the next generation in autonomous racing. It comes fully equipped with stereo cameras and LiDAR sensor to enable object avoidance and head-to-head racing, giving developers everything they need to take their racing to the next level. In object avoidance races, developers use the sensors to detect and avoid obstacles placed on the track. In head-to-head, developers race against another DeepRacer on the same track and try to avoid it while still turning in the best lap time. Forward facing left and right cameras make up the stereo cameras, which helps the car learn depth information in images. This information can then be used to sense and avoid objects being approached on the track. The LiDAR sensor is backward facing and detects objects behind and beside the car.
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Under the hood
The AWS DeepRacer Evo car includes the original AWS DeepRacer car, an additional 4 megapixel camera module that forms stereo vision with the original one, a scanning LiDAR, a shell that can fit both the stereo camera and LiDAR, and a few accessories and easy-to-use tools for a quick installation.
| CAR | 18th scale 4WD with monster truck chassis |
| CPU | Intel Atom™ Processor |
| MEMORY | 4GB RAM |
| STORAGE |
32GB (expandable) |
| WI-FI | 802.11ac |
| CAMERA | Stereo 4 MP cameras with MJPEG |
| LIDAR Sensor | 360 Degree 12 Meters Scanning Radius LIDAR Sensor |
| SOFTWARE | Ubuntu OS 16.04.3 LTS, Intel® OpenVINO™ toolkit, ROS Kinetic |
| DRIVE BATTERY | 7.4V/1100mAh lithium polymer |
| COMPUTE BATTERY | 13600mAh USB-C PD |
| PORTS | 4x USB-A, 1x USB-C, 1x Micro-USB, 1x HDMI |
| SENSORS | Integrated accelerometer and gyroscope |
Explore the portfolio of educational devices designed for developers of all skill levels to learn ML in fun, practical ways. Get started with reinforcement learning with AWS DeepRacer, learn how to build deep learning-based computer vision apps with AWS DeepLens, and express your creativity through generative AI with AWS DeepComposer.
