Amazon Web Services (AWS) has announced a new IoT-based platform that signals an expansion into robotic fleet management.
IoT RoboRunner, which was revealed on the first day of the company's annual Re:Invent conference, is designed to help enterprises build and deploy applications so that their robotic fleets all operate as one.
RoboRunner is an expansion of the RoboMaker cloud-based simulation service launched in 2018. It addressed developer frustrations around the challenge of operating different robot types, such as autonomous guided vehicles (AGV) and robotic manipulators.
"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," AWS principal developer advocate, Channy Yun said.
"AWS IoT RoboRunner lets you connect your robots and work management systems, thereby enabling you to orchestrate work across your operation through a single system view."
RoboRunner includes tools to create a programme in the AWS Management Console to build repositories for storing robot and task data. Developers can also integrate codes for connecting robots and systems via RoboRunner's Fleet Gateway Library and also tools from managed applications services such as AWS Lambda and Greengrass.
Additionally, the cloud giant has also launched the AWS Robotics Startup Accelerator, which will offer mentorship to robotics startups. This accelerator will include a four-week programme with hands-on AWS training and $10,000 in promotional credits for use of AWS services.
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The first day of Re:Invent saw a plethora of new services launched for AI, machine learning, storage and quantum computing.
Amazon Braket Hybrid Jobs, for example, was launched as a new offering to help reduce extensive infrastructure and software management and confidently execute algorithms quickly and predictably, with on-demand priority access to QPUs.
There was also an expansion of CodeGuru Reviewer with an automated tool to help developers detect secrets in source code or configuration files, such as passwords or access tokens.
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