Introducing Amazon SageMaker Kubeflow Reinforcement Learning Pipelines for Robotics

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Robots require the integration of technologies such as image recognition, sensing, artificial intelligence, machine learning (ML), and reinforcement learning (RL) in ways that are new to the field of robotics. Orchestrating robotics operations to train, simulate, and deploy RL applications is difficult and time-consuming. Now, with AnyScale’s Ray and SageMaker RL components and pipelines, it’s faster to experiment and manage robotics RL workflows from perception to controls and optimization, and create end-to-end solutions without having to rebuild each time. In this talk, we will talk about two use cases utilizing AnyScale’s Ray with SageMaker RL Kubeflow components where 1) Woodside Energy uses AnyScale’s Ray with an external cloud simulator, AWS RoboMaker, to start exploring using machine learning methods for robotics manipulation for power plant operations, and 2) General Electric Aviation uses AnyScale’s Ray with an open-source simulator, PyBullet, to improve manufacturing plant operations.