What techniques does AWS use for the AWS DeepRacer?

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.

What is AWS DeepRacer challenge?

Welcome to the world’s first global autonomous racing league, driven by reinforcement learning. It’s time to race for prizes, glory, and a chance to advance to compete for the AWS DeepRacer Championship Cup. Submit your models and compete from anywhere in the world!

What machine learning algorithm is AWS DeepRacer using?

The AWS DeepRacer console uses a neural network to model the policy learned by both PPO and SAC. The output of the policy is a discrete set of values.

How do you analyze DeepRacer logs?

To prepare the data that we want to analyze, we have to download our model training logs from the AWS DeepRacer console.

1. On the AWS DeepRacer console, under Reinforcement learning, choose Your models.
2. Choose the model to analyze.
3. In the Training section, under Resources, choose Download Logs.

How can I improve my AWS DeepRacer?

Take aways

1. play around with the reward function and use the simulation movie to judge how it affects your car’s behavior.
2. train the model on different racing courses to get a stable behavior.
3. more complex reward functions and more movement possibilities set in the DeepRacer UI increase training time.

What is AWS RoboMaker?

AWS RoboMaker is a cloud-based simulation service that enables robotics developers to run, scale, and automate simulation without managing any infrastructure.

What is DeepRacer learning rate?

And for smaller batch sizes, the epoch can be small while for larger batches, this can have a larger value. Learning rate is the one which is important of all the hyperparameters. The default learning rate of 0.003 is good enough but we can still increase or decrease it depending on our requirement.

Does Amazon use Ros?

Amazon Web Services (AWS) Robotics has released an introductory Cloud Robotics Curriculum designed to help students, educators, and entry level developers build robotics applications with Robot Operating System (ROS) and AWS RoboMaker.

Is AWS RoboMaker free?

AWS RoboMaker cloud extensions for ROS are free and released under the Apache Software License 2.0, a permissive license with limited restrictions on reuse. You only incur standard AWS service charges when your ROS application utilizes AWS services through these cloud extensions.

How can I improve my DeepRacer model?

Optimize Training AWS DeepRacer Models for Real Environments

1. Make sure that your vehicle is well calibrated.
2. Test your vehicle with the default model first.
3. Make sure the model works in simulation.
4. Do not over train the model.
5. Use multiple models from different iterations.

Is ROS2 better than ROS?

Unless your paper concern ROS2 performance or features you should stick with ROS for now. You should really consider ROS2 to reduce the amount of code transfer in the future. Put people with experience with ROS on the project.

What features does the AWS deepracer service support?

The AWS DeepRacer service supports the following features: Train a reinforcement learning model on the cloud. Evaluate a trained model in the AWS DeepRacer console. Submit a trained model to a virtual race and, if qualified, have its performance posted to the event’s leaderboard.

What is a reward function in deep racer?

For AWS DeepRacer, an action corresponds to a vehicle move at a particular speed and steering angle. Reward. The reward is the score given as feedback to the agent when it takes action in a given state. In training the AWS DeepRacer model, the reward is returned by a reward function.

What is the performance metric in deepracer?

The performance metric depends on the race type. It can be the fastest lap time, total time, or average lap time submitted by AWS DeepRacer users who have evaluated their trained models on a track identical or similar to the given track of the race.