AWS Robotics Blog

Build applications to help robots work together with AWS IoT RoboRunner

We’re excited to announce the preview of AWS IoT RoboRunner, a new robotics service that makes it easier for enterprises to build and deploy applications that help fleets of robots work together seamlessly. With AWS IoT RoboRunner, you can connect your robots and work management systems enabling you orchestrate work across your operation through a single system view. This new service builds on the same technology used in Amazon fulfillment centers and now we are excited to make it available to all developers to build advanced robotics applications for their businesses. In this blog, I will provide an overview of AWS IoT RoboRunner, and how you can get started for your own robotic fleets.

The challenge: Using Robots at Scale

Enterprises increasingly rely on robots to automate their operations in warehouse facilities, fulfillment centers, and factories. Many customers choose different types of robots – often from different vendors in a single facility. For example, picking and sorting consumer goods in fulfillment centers, moving inventory in a warehouse, preparing items for shipping or stowage, etc. As enterprises scale the number of robots in operation, complexity increases and it becomes more and more difficult to manage and orchestrate these robots efficiently. Enterprises want to manage through the complexity and build applications that allow them to manage their robot fleets distinctly, but face several obstacles to building those applications. Because each robot vendor and work management system has its own control software, data format, and data repository, it’s difficult for developers to unify the data that is required to build applications that work across fleets of robots. When a new robot is added to an autonomous operation, complex and time-consuming software integration work is required to connect the robot control software to work management systems. Lastly, when data is unified and integrated with central management systems, it’s difficult and time consuming for developers to define and program logic for complex management applications such as robot task orchestration.

Now, with AWS IoT RoboRunner it’s easier to build applications that make it possible to interoperate and orchestrate robots from a single view by removing complex development work required to connect robots to each other and the rest of your industrial software systems. AWS IoT RoboRunner collects and combines data from each type of robot in a fleet and standardizes data types like facility, location, and robotic task data in a central repository to make it easier to build robotic management applications for fleets of robots. Developers can use AWS IoT RoboRunner to access the unified data required to build complex management applications for fleets of robots and use pre-built software libraries to build applications for common robot orchestration tasks that include built-in functions for shared-space management and work allocation. Robotics applications built with AWS IoT RoboRunner can integrate with AWS IoT SiteWise for metrics, Amazon SageMaker for machine learning-based task allocation, AWS IoT Greengrass for building, deploying, and managing the device software. Using AWS IoT RoboRunner, robotics developers no longer need to manage robots in silos and can more effectively automate tasks across a facility with centralized control.

AGCO is global leader in design, manufacture, and distribution of agricultural machinery and operates a robot fleet for material handling. “With AWS IoT RoboRunner we will further increase our shop floor productivity and our ability to better cope with increased complexity and greater diversity of robots. Our partnership with AWS will accelerate our path towards autonomous material flow,’ said Hubertus Koehne, Vice President of Smart Manufacturing and Innovation.

Getting started with AWS IoT RoboRunner

To get started with AWS IoT RoboRunner, navigate to the AWS console and create a representation of the work area as a “Site”, which is a logical construct defined in AWS IoT RoboRunner to represent a facility. The robots working on this site are then setup in AWS IoT RoboRunner as a “Fleet”. A fleet represents a group of robots working under the same fleet management system, and each individual robot is setup in AWS IoT RoboRunner as a “Robot” within a fleet.

To send and receive data from individual robot fleet managers, AWS IoT RoboRunner implements “Fleet connectors” so that it can communicate with different fleet managers in the same format, and interpret and send tasks to all these systems. These fleet connectors are edge components deployed on-premises at facilities using AWS IoT Greengrass, or are deployed in the cloud if the fleet managers are connected to the cloud.

Next, setup connectors so that AWS IoT RoboRunner can receive the tasks needed to execute, from task sources such as enterprise work management systems. AWS IoT RoboRunner provides sample code for allocating tasks to robot fleets so that you can get started quickly. You can customize the task allocation code with business rules that align to your use case.

And finally, to enable a single system view of the robots, status of the systems, and progress of tasks on the same interface, AWS IoT RoboRunner provides API’s that enable you to build a user application. The AWS IoT RoboRunner API’s can also be used to create the metrics and KPIs that customers need to track.

Partner integration

To make it easy to implement AWS IoT RoboRunner with existing operations, we have partnered with systems integrators such as Accenture, Cognizant, Fresh Consulting, and Slalom Consulting who can offer you on-site integration services. Our partners can work with you to build an interface between AWS IoT RoboRunner and the backend enterprise systems used to issue tasks and missions to your robots, or your frontend user-facing applications for capabilities like mobile robot visualization and fault alerting system.

Accenture is a global professional services company with leading capabilities in digital, cloud and security. “Our clients are demanding faster and easier solutions to combine diverse robotic systems and deploy them across their networks of manufacturing facilities and warehouses,” said Joe Lui, global robotics practice lead for Industry X at Accenture, “AWS IoT RoboRunner can make it significantly less complex for clients to integrate and orchestrate robotic systems from different providers, ensuring all robotic systems are working seamlessly together.”

Cognizant is one of the world’s leading professional services companies, transforming clients’ business, operating and technology models for the digital era. Sharath Prasad, AVP of the IoT Practice Industry+ at Cognizant said, “Warehouses are adopting digital technologies such as advanced automation to improve operational efficiencies. Cognizant’s APEx Accelerator has delivered operational improvements in factories, and we intend to extend this to address digital transformations in warehouses and distribution centers. APEx leverages AWS IoT and will now include AWS IoT RoboRunner, with its information & data models, to provide an integration platform to connect a variety of robotic systems for material handling with the AWS Cloud.”


In this blog, we discussed the challenges of managing a robot fleets with robots from multiple vendors and walked through how AWS IoT RoboRunner makes it easier to build applications for managing and orchestrating robots. As we look to the future, we see more companies adding more robots of more types.  Harnessing the power of all those robots is complex, but we are dedicated to helping enterprises get the full value of their automation by making it easier to optimize robots through a single system view. If you are using robots from different brands in a single facility, facing the issues we have outlined here, and want to know more about how AWS IoT RoboRunner can help you, contact us or one of our partners listed here.

AWS IoT RoboRunner is available in Preview and can be accessed through the AWS Console.