Learning Steering Bounds for Parallel Autonomous Systems

Learning Steering Bounds for Parallel Autonomous Systems

Deep learning has been successfully applied to "end-to-end" learning of the autonomous driving task, where a deep neural network learns to predict steering control commands from camera data input. While these previous works support reactionary control, the representation learned is not usa...

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Bibliographic Details
Main Authors: Amini, Alexander A (Contributor), Paull, Liam (Contributor), Balch, Thomas M (Contributor), Karaman, Sertac (Contributor), Rus, Daniela L (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Department of Mathematics (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Amini, Alexander (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2018-09-05T11:56:52Z.
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