Robots are being used more widely in society for purposes that are increasing in sophistication such as complex assembly, picking and packing, last-mile delivery, environmental monitoring, search and rescue, and assisted surgery. Within the autonomous mobile robot (AMR) and autonomous ground vehicle (AGV) market segments, robots are being used for commercial logistics and consumer cleaning, delivery, and companionship.
These jobs require higher compute capabilities and often the orchestration of the deployment and operations of large fleets of robots. To function effectively, the robots require the integration of technologies such as image recognition, sensing, artificial intelligence, machine learning, and reinforcement learning in ways new to the field of robotics. Until now, developing, simulating, deploying and managing such smart robotics applications was a difficult and time consuming. Now, with AWS RoboMaker, it is easy to enable a robot running ROS to navigate, communicate, comprehend, stream data, and learn. Tasks that once could either not be done or took months can now be done in hours or days.
Benefits and Customer Results
AWS RoboMaker is the most complete cloud solution for robotic developers to simulate, test and securely deploy robotic applications at scale. RoboMaker provides a fully-managed, scalable infrastructure for simulation that customers use for multi-robot simulation and CI/CD integration with regression testing in simulation. In addition, AWS RoboMaker provides an IDE, fleet management capabilities, ROS extensions, and seamless integration with various Amazon and AWS services to empower customers to innovate and provide best-of-class robotic solutions. RoboMaker's managed ROS and Gazebo software stacks free up engineering resources and enable you to start building quickly.
Get started quickly
AWS RoboMaker includes sample robotics applications to help you get started quickly. These provide the starting point for the voice command, recognition, monitoring, and fleet management capabilities that are typically required for intelligent robotics applications. Sample applications come with robotics application code and simulation application code. The sample simulation applications come with pre-built worlds such as indoor rooms, retail stores, and racing tracks so you can get started in minutes.
Build intelligent robots
Easily integrate powerful machine learning, voice recognition, and language processing capabilities to your robotics applications with a suite of AWS services for building end to end solutions. RoboMaker provides extensions for cloud services like Amazon Kinesis (video stream), Amazon Rekognition (image and video analysis), Amazon Lex (speech recognition), Amazon Polly (speech generation), and Amazon CloudWatch (logging and monitoring) to developers who are using Robot Operating System, or ROS.
Simulation and Fleet Management Capabilities
Using AWS RoboMaker fleet management, you can deploy an application to a fleet of robots and with RoboMaker simulation capabilities you can easily simulate and virtually test robotics applications in various environments. Using the CloudWatch metrics and logs extension for ROS, you can monitor these robots throughout their lifecycle to understand CPU, speed, memory, battery, and more. When a robot needs an update, you can use RoboMaker simulation for regression testing before deploying the fix or new feature through RoboMaker fleet management.
Increase code quality and release velocity while improving test coverage. With AWS RoboMaker, iRobot now runs more than 40 automated tests on each code commit and more than 500 automated tests for each release candidate).
Using AWS RoboMaker, Bastian Solutions easily built a Gazebo simulation environment with more than 35 robots in a fleet to test multi-robot orchestration.
With AWS RoboMaker, Takenaka is able to generate maps for multiple building layouts and deploy to construction site robots without needing to operate, test and train to robots locally first.