Nvidia Corporation

Claire Delaunay

Gary D Hicok

Michael Brian Cox

John R Zedlewski

Rev Lebaredian

Tony Tamasi

Greg Heinrich

David Weikersdorfer

Clement Farabet

Gregor Markus Kopka

Zachary Taylor

Mark Daly

Matthew Campbell

David Auld

Gabriele Pasqualino

Kenneth William MacLean

Curtis A Beeson

Curtis Beeson

Robot

In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.

Training, testing, and verifying autonomous machines using simulated environments

In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment&#x2014;in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack&#x2014;to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.

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Menlo Park, CA, United States of America

Claire Delaunay