Learning an Explainable Trajectory Generator Using the Automaton Generative Network
Invention type: Technology
/
Case number: #23571J
Researchers
Daniela Rus
/
Guy Rosman
/
Sertac Karaman
/
Minoru Araki
/
Igor Gilitschenski
/
Cristian-Ioan Vasile
/
Xiao Li
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
-
method for learning an explainable trajectory generator using an automaton generative network
United States of America | Published application
License this technology
Interested in this technology? Connect with our experienced licensing team to initiate the process.
Sign up for technology updates
Sign up now to receive the latest updates on cutting-edge technologies and innovations.