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.
Sahika Genc is a principal applied scientist at Amazon artificial intelligence (AI). Her research interests are in smart automation, robotics, predictive control and optimization, and reinforcement learning (RL), and she serves in the industrial committee for the International Federation of Automatic Control. She leads science teams in scalable autonomous driving and automation systems, including consumer products such as AWS DeepRacer and SageMaker RL. Previously, she was a senior research scientist in the Artificial Intelligence and Learning Laboratory at the General Electric (GE) Global Research Center, where she led science teams on healthcare analytics and collaborated with government organizations and research institutions to develop energy analytics for consumers and utilities, served in the organizing committees for the American Control Conference, and was an associate editor for IEEE Transactions on Automation Science and Engineering. She has more than 30 patents and 50 conference, journal, and technical report publications. She earned her MS and PhD degrees in electrical engineering systems from the University of Michigan-Ann Arbor.