Learning an Explainable Trajectory Generator Using the Automaton Generative Network
Invention type: Technology
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Case number: #23571J
Researchers
Daniela Rus
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Xiao Li
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Cristian-Ioan Vasile
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Igor Gilitschenski
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Minoru Araki
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Sertac Karaman
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Guy Rosman
Departments: Dept of Electrical Engineering & Computer Science, Department of Aeronautics and Astronautics
Technology Areas: Artificial Intelligence (AI) and Machine Learning (ML) / Computer Science: Networking & Signals
Impact Areas: Advanced Materials
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method for learning an explainable trajectory generator using an automaton generative network
United States of America | Granted | 12,024,203
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