AWS Robotics Blog

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Containerize robot applications for testing in the cloud and deploying at the edge

Robotics developers use the open source Robot Operating System (ROS) to build distributed and complex applications for their robots. Robot developers benefit from using the cloud for building, training, and testing robotic applications at scale with Continuous integration and continuous deployment (CI/CD) workflows for physical testing and updates pushed over the air. Containers provide a […]

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Build and simulate a Mini Pupper robot in the cloud without managing any infrastructure

AWS RoboMaker provides a comprehensive cloud solution for robotics development. It features fully managed simulation capabilities built on scalable infrastructure. In this post, we use a simple Mini Pupper sample application to demonstrate how to use AWS RoboMaker for robotics application development, testing, and simulation.

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Boston Dynamics Spot Robot

How Boston Dynamics and AWS use mobility and computer vision for dynamic sensing

AWS and Boston Dynamics are working together to bring dynamic sensing to life, taking sensors where they’re needed through mobile robots and using AWS tools to process the data into critical insights for industrial teams. AWS IoT Greengrass 2.0 is an open-source edge runtime that is compatible with Spot’s compute payloads and enables delivery and execution of applications or ML models on the robot. AWS IoT Greengrass also enables Spot to send data back to the cloud with flexibility for varied use-cases.

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Accelerating the pace of innovation with robotics startups and AWS

To support the robotics start-up community, AWS invited early-stage robotics startups for a three-day program to learn and build with AWS Robotics business and technical experts. The AWS Robotics Startup Acceleration program was held virtually, August 17-August 19, 2021 with founders and technical executives from robotics startups. 

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Deploy and Manage ROS Robots with AWS IoT Greengrass 2.0 and Docker

In this blog, we introduce a new way to deploy and manage robot software on production fleets at scale using AWS IoT Greengrass 2.0. When combined with the industry-grade tools, libraries, and capabilities of the Robot Operating System 2 (ROS2), developers can bring new cloud-enhanced robot features to market, and reduce the time and effort required to build failure-resilient infrastructure. 

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AWS RoboMaker now supports ROS2 Foxy Fitzroy featuring Navigation2

AWS RoboMaker now supports ROS 2 Foxy Fitzroy (Foxy), enabling developers to use Foxy during development or simulation. In ROS 2, Navigation2 (Nav2) is the second generation of the ROS Navigation software stack, enabling robots to move autonomously from point A to B. Nav2 includes new features not previously available in ROS that help developers improve the performance of their robot’s navigation and enables new robotics use cases within logistics, hospitals, or security. In this blog, I review Nav2 features and architecture, and show you how to use Nav2 in AWS RoboMaker.

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Picture of the Spot Robot in Simulation

Clearpath enables robotics prototyping with one-click simulations using AWS

AWS helps Clearpath Robotics make it easier for their customers like Boston Dynamics to prototype robotics applications in simulation. With the AWS CloudFormation Launch Stack, Clearpath’s customers can launch Gazebo simulations in AWS RoboMaker with a click of a button.  

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Cloud Robotics

Deploying ROS applications as Snaps with AWS IoT Greengrass 2.0

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.

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Introducing upload configurations for AWS RoboMaker Simulation

Introduction AWS RoboMaker now supports data upload configurations within simulation jobs. This capability allows developers to define the type of simulation data they want to upload, choose the upload behavior, and reliably upload the simulation data to their preferred Amazon S3 output location. This functionality makes it easier for developers to review or analyze application […]

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