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
Build and train models using Amazon SageMaker under the hood. Test and iterate in the AWS DeepRacer 3D simulation environment. No coding experience required.
Experience the thrill of the race in the real-world when you deploy your reinforcement learning model onto AWS DeepRacer.
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.
Get rolling with machine learning
With AWS DeepRacer you'll learn fundamental concepts, skills, and machine learning (ML) training techniques that power foundation models in some of the most advanced generative AI applications today; through the fun of racing autonomous cars. AWS DeepRacer gives you a fun and hands-on way to learn to train ML models, where you can see your training come to life by deploying your model onto a preconfigured autonomous RC car and miniature race track.
Test model training fundamentals using 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.
Compete for prizes and meet fellow ML enthusiasts in the AWS DeepRacer League. Connect with the global community to share ideas and insights and even host your own virtual races with racer organizer tools.
The AWS DeepRacer storefront on amazon.com offers everything you need to host an in-person race, from cars to tracks and batteries to zip ties—making race planning simple so you can focus on racing!
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 2024!
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 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.
Dive deeper into model training with 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.
Already own an AWS DeepRacer?
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 |
