AWS RoboMaker is a service that makes it easy to develop, test, and deploy intelligent robotics applications at scale. RoboMaker extends the most widely used open-source robotics software framework, Robot Operating System (ROS), with connectivity to cloud services. This includes AWS machine learning services, monitoring services, and analytics services that enable a robot to stream data, navigate, communicate, comprehend, and learn. RoboMaker provides a robotics development environment for application development, a robotics simulation service to accelerate application testing, and a robotics fleet management service for remote application deployment, update, and management.
Robots are machines that sense, compute, and take action. Robots need instructions to accomplish tasks, and these instructions come in the form of applications that developers code to determine how the robot will behave. Receiving and processing sensor data, controlling actuators for movement, and performing a specific task are all functions that are typically automated by these intelligent robotics applications. Intelligent robots are being increasingly used in warehouses to distribute inventory, in homes to carry out tedious housework, and in retail stores to provide customer service. Robotics applications use machine learning in order to perform more complex tasks like recognizing an object or face, having a conversation with a person, following a spoken command, or navigating autonomously. Until now, developing, testing, and deploying intelligent robotics applications was difficult and time consuming. Building intelligent robotics functionality using machine learning is complex and requires specialized skills. Setting up a development environment can take each developer days and building a realistic simulation system to test an application can take months due to the underlying infrastructure needed. Once an application has been developed and tested, a developer needs to build a deployment system to deploy the application into the robot and later update the application while the robot is in use.
AWS RoboMaker provides the tools to make building intelligent robotics applications more accessible, a fully managed simulation service for quick and easy testing, and a deployment service for lifecycle management. AWS RoboMaker removes the heavy lifting from each step of robotics development so you can focus on creating innovative robotics applications.
How it works
AWS RoboMaker provides four core capabilities for developing, testing, and deploying intelligent robotics applications.
Cloud Extensions for ROS
Robot Operating System, or ROS, is the most widely used open source robotics software framework, providing software libraries that help you build robotics applications. AWS RoboMaker provides cloud extensions for ROS so that you can offload to the cloud the more resource-intensive computing processes that are typically required for intelligent robotics applications and free up local compute resources. These extensions make it easy to integrate with AWS services like Amazon Kinesis Video Streams for video streaming, Amazon Rekognition for image and video analysis, Amazon Lex for speech recognition, Amazon Polly for speech generation, and Amazon CloudWatch for logging and monitoring. RoboMaker provides each of these cloud service extensions as open source ROS packages, so you can build functions on your robot by taking advantage of cloud APIs, all in a familiar software framework.
AWS RoboMaker provides a robotics development environment for building and editing robotics applications. The RoboMaker development environment is based on AWS Cloud9, so you can launch a dedicated workspace to edit, run, and debug robotics application code. RoboMaker's development environment includes the operating system, development software, and ROS automatically downloaded, compiled, and configured. Plus, RoboMaker cloud extensions and sample robotics applications are pre-integrated in the environment, so you can get started in minutes.
Simulation is used to understand how robotics applications will act in complex or changing environments, so you don’t have to invest in expensive hardware and set up of physical testing environments. Instead, you can use simulation for testing and fine-tuning robotics applications before deploying to physical hardware. AWS RoboMaker provides a fully managed robotics simulation service that supports large scale and parallel simulations, and automatically scales the underlying infrastructure based on the complexity of the simulation. RoboMaker also provides pre-built virtual 3D worlds such as indoor rooms, retail stores, and race tracks so you can download, modify, and use these worlds in your simulations, making it quick and easy to get started.
Once an application has been developed or modified, you’d build an over-the-air (OTA) system to securely deploy the application into the robot and later update the application while the robot is in use. AWS RoboMaker provides a fleet management service that has robot registry, security, and fault-tolerance built-in so that you can deploy, perform OTA updates, and manage your robotics applications throughout the lifecycle of your robots. You can use RoboMaker fleet management to group your robots and update them accordingly with bug fixes or new features, all with a few clicks in the console.
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 (instructions for the functionality of your robot) and simulation application code (defining the environment in which your simulations will run). 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. You can modify and build on the code of the robotics application or simulation application in the development environment or use your own custom applications.
Build intelligent robots
Because AWS RoboMaker is pre-integrated with popular AWS analytics, machine learning, and monitoring services, it’s easy to add functions like video streaming, face and object recognition, voice command and response, or metrics and logs collection to your robotics application. 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. These services are exposed as ROS packages so that you can easily use them to build intelligent functions into your robotics applications without having to learn a new framework or programming language.
Manage the lifecycle of a robotics application from building and deploying the application, to monitoring and updating an entire fleet of robots. Using AWS RoboMaker fleet management, you can deploy an application to a fleet of robots. 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.
NASA Jet Propulsion Laboratory creates and works with many robots and rovers to explore space terrain. By using AWS RoboMaker, JPL is able to visualize their open source rover and receive near-real time metrics to understand how it’s functioning. AWS RoboMaker simulation has also enabled JPL to accelerate development of new functionality for the rover, for example by testing a robotic arm that can mimic the arm movements of a human.
“AWS RoboMaker exponentially increases the capabilities of Lea, an autonomous robot assistant for the elderly and disabled. Lea is interactive, keeps elderly safe and active, while it can talk to you, navigate around your house and keep you connected with family and doctors. We have used AWS RoboMaker cloud extensions for ROS to enhance Lea with video and telemetry data streaming, and voice interaction capabilities using services like Amazon Kinesis, Amazon Lex, and Amazon Polly. These cloud services and extensions provided by AWS RoboMaker have enabled us to rapidly develop new features, while breaking the limitations of small on-board computing power.”
- Dimitrios Chronopoulos, Lead Mobility Engineer, Robot Care Systems
“We are planning to use autonomous ground vehicles and drones to make the construction industry more productive while reducing construction rework costs. Using a variety of imaging sensors, the collected data can be used to create 3D site models for planning and streamlining construction activities. With AWS RoboMaker, we are able to easily test the robotics related software applications in a cloud environment, and rapidly generate synthetic imaging data to train our 3D site model creation algorithms. AWS RoboMaker also provides the ideal fleet management solution for use on ground vehicles and drones. The integration between AWS RoboMaker fleet management and AWS Greengrass makes it really easy to enable communications among ground vehicles, drones, and IoT solutions.”
- Hamid Montazeri, VP of SW Engineering and Robotics, Stanley Black & Decker
FIRST designs accessible, innovative programs that build not only science and technology skills and interests, but also self-confidence, leadership, and life lessons. “We’re excited to utilize AWS RoboMaker, helping make it easier for students of all ages to develop, test, and deploy robotic applications. Offerings like these make it easier for FIRST to meet its mission – to inspire young people to be science and technology leaders and innovators by engaging them in mentor-based, science-focused programs.”
- Don Bossi, President, FIRST
Open Robotics works with industry, academia, and government to create and support open source software for the global robotics industry, from R&D to commercial deployments. “AWS's support for our products, including ROS 2, will significantly advance our goal of making open platforms the basis for all robotics applications. With ROS and Gazebo available via AWS, it's now easier than ever for developers to get started and for companies to integrate these tools into their workflow. I can't wait to see the new and innovative ROS-based robots that will be developed.”
- Brian Gerkey, CEO, Open Robotics
"As a leader in robot strategy, sales, and support, we have been connecting our customers with advanced robots across the globe, from enterprise conferences to airports and the Olympics, to create engaging experiences. We provide engineering resources, and work in partnership with robot manufacturers to create custom robotics applications. We use and recommend AWS RoboMaker because it helps us rapidly prototype and increase the speed of delivery for intelligent robotics functions like voice interaction and wayfinding, resulting in more compelling user experiences for our customers. We are excited to be a RoboMaker partner and look forward to using RoboMaker services across our robot portfolio."
- Paul McManus, CEO, Advance Robot Solutions
Research and education partners
"GTRI’s research in collaborative autonomy enables heterogeneous teams of robots to work together to accomplish mission objectives without the need for a human in the loop. Autonomous behaviors include onboard path planning through cluttered environments, efficient distribution of tasking, and sharing of sensor data for a common world view. AWS RoboMaker offers the ability to host our simulations in a powerful and accessible way, and to leverage tools and environmental models not available in more limited systems. We view this ability to simulate complex behaviors and interactions in a realistic simulation as critical to the development of powerful new algorithms and techniques."
- Don Davis, Division Chief, Robotics and Autonomous Systems, Georgia Tech Research Institute