Ford Global Technolgoies, LLC

Francis Assadian

Iman Soltani Bozchalooi

Lisa Scaria

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine performance of a plurality of vehicle data sources used to operate a vehicle by evaluating each vehicle data source output data and train a deep neural network to determine reliability for each of the vehicle data sources based on the performance using reinforcement learning. The instructions can further include instructions to combine output data from the vehicle data sources based on the reliability including using the deep neural network to correlate output data from one or more vehicle data sources to the performance to determine how accurately the output data from each vehicle data source corresponds to vehicle performance and operate the vehicle based on combined output data.

Adaptive sensor fusion

A method of acquiring and processing visual data is provided, which includes: directing a light of a particular color to at least one of the plurality of landmarks on an object to illuminate the at least one of the plurality of landmarks; obtaining a first image of the object when the at least one of the plurality of landmarks on the object is illuminated; and extracting coordinates of the at least one of the plurality of landmarks from the first image.

High-throughput automated annotation of visual data for training neural networks used for landmark detection

An automation system includes a manipulation system including a manipulator for moving an object to a target location, a vision system for detecting landmarks on the object and the target location, and a learning and control module. The vision system is movable. The learning and control module is configured to control a movement of the manipulator and change a field of view of the vision system independent of the movement of the manipulator.

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Davis, CA, United States of America

Francis Assadian