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公开(公告)号：US20210325891A1
公开(公告)日：2021-10-21
申请号：US17232818
申请日：2021-04-16
Applicant: Raytheon Company
Inventor： Darrell L. Young , Christopher A. Eccles , Franklin Tanner
Abstract: Discussed herein are devices, systems, and methods for autonomous, dynamic navigation of scenarios. A method can include implementing a path generation machine learning (ML) technique to determine paths between a device and a goal, determining a node of the paths as an intersection of at least two of the paths, and implementing an executive ML technique to determine which of the at least two paths to take at a node of the graph to reach the goal.
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公开(公告)号：US11562184B2
公开(公告)日：2023-01-24
申请号：US17181581
申请日：2021-02-22
Applicant: Raytheon Company
Inventor： Jonathan Goldstein , Steven J. Shumadine , Christopher A. Eccles
Abstract: A computer obtains image frames. The computer identifies a chip within the image frames, the chip having a position and dimensions determined based on a lane width. Based on a speed and a length of a vehicle passing through a field of view of the camera, the computer selects a subset of the image frames. The computer takes, from each of the image frames in the subset, the identified chip for use as input to an artificial neural network (ANN). The computer individually provides each taken chip as input to the ANN to generate an ANN output. Based on a combination of the ANN outputs, the computer identifies a shape, a number of axles, and a number of segments of the vehicle. The computer provides a tuple representing the vehicle shape, the number of axles, and the number of segments.
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公开(公告)号：US20220269899A1
公开(公告)日：2022-08-25
申请号：US17181581
申请日：2021-02-22
Applicant: Raytheon Company
Inventor： Jonathan Goldstein , Steven J. Shumadine , Christopher A. Eccles
Abstract: A computer obtains image frames. The computer identifies a chip within the image frames, the chip having a position and dimensions determined based on a lane width. Based on a speed and a length of a vehicle passing through a field of view of the camera, the computer selects a subset of the image frames. The computer takes, from each of the image frames in the subset, the identified chip for use as input to an artificial neural network (ANN). The computer individually provides each taken chip as input to the ANN to generate an ANN output. Based on a combination of the ANN outputs, the computer identifies a shape, a number of axles, and a number of segments of the vehicle. The computer provides a tuple representing the vehicle shape, the number of axles, and the number of segments.
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