AWS Robotics Blog

AWS RoboMaker, a service that allows developers to simulate robotics applications at cloud scale, now supports using containers to run any robot and simulation software of their choice, and provides Graphics Processor Unit (GPU) support for high-fidelity simulation. Now, developers can simulate workloads in AWS RoboMaker that require high-fidelity graphics such as autonomous driving and machine learning. In this blog, you will learn how to use new AWS RoboMaker features to test autonomous vehicles in the CARLA autonomous driving simulator, a high-fidelity simulator based on Unreal Engine.

This blog uses colcon bundle for robot and simulation applications. AWS RoboMaker now only supports containers to make it easy for you to bring and run your own simulations and applications. To follow along with this blog post, see our updated blog on Preparing ROS application and simulation application containers for AWS RoboMaker. Introduction Roboticists test […]

This blog references AWS RoboMaker Fleet Management, a feature that has been deprecated. You should now use AWS IoT Greengrass V2 for deploying and managing your robot software. To learn more about this process, see our blog on how to Deploy and manage ROS robots with AWS IoT Greengrass 2.0 and Docker. Introduction An increasingly […]

This blog references AWS RoboMaker Fleet Management, a feature that has been deprecated. You should now use AWS IoT Greengrass V2 for deploying and managing your robot software. To learn more about this process, see our blog on how to Deploy and manage ROS robots with AWS IoT Greengrass 2.0 and Docker. Introduction AWS RoboMaker […]

This blog uses colcon bundle for robot and simulation applications. AWS RoboMaker now only supports containers to make it easy for you to bring and run your own simulations and applications. To follow along with this blog post, see our updated blog on Preparing ROS application and simulation application containers for AWS RoboMaker. Introduction Building […]

The S3 rosbag cloud extension enables customers to easily configure and record data from robots as rosbags, and upload them to Amazon S3, which they can later use to analyze events, troubleshoot existing applications, and provide as inputs to AWS RoboMaker log-based simulation for regression. In this blog, we will review three ROS nodes in the S3 rosbag cloud extension that create and upload rosbag files from the robot to Amazon S3, with hands-on examples of how to use the nodes.

This blog references AWS RoboMaker Integrated Development Environment (IDE), a feature that has been deprecated. To follow along with this blog post, use the AWS Cloud9 IDE. See our updated blog on how to Build and simulate robotics applications in AWS Cloud9. Introduction Alexa is Amazon’s cloud-based voice service and Alexa-compatible devices allow users to […]

In this blog, we walk you through the steps required to train a machine learning model using RL on AWS RoboMaker. Specifically, we familiarize you with the development environment, then define the steps required to complete RL machine learning within AWS RoboMaker.

In this blog, learn about AWS RoboMaker WorldForge, and how 3D world generation can be used to streamline testing and training of core robotic algorithms at scale.

AWS recently announced the release of AWS IoT Greengrass 2.0, an edge runtime that offers added flexibility in deploying containerized applications than its predecessor. In this blog, we’ll explore why this improvement is useful for the robotics community, and walk through how you package and deploy Robot Operating System (ROS) applications to devices using AWS IoT Greengrass 2.0.