Industrial vehicle with feature-based localization and navigation
First Claim
1. A system comprising a vehicle camera, and a navigation module, wherein:
- the vehicle camera is communicatively coupled to the navigation module and is configured to capture input images of a warehouse;
the navigation module is configured to distinguish between object types in the input images by executing machine readable instructions tocreate Gaussian scale space pyramids from the input images of the warehouse,build determinant of Hessian response pyramids from the Gaussian scale space pyramids,build trace of Hessian response pyramids from the Gaussian scale space pyramids,utilize the determinant of Hessian response pyramids to identify candidate object types in the input images,utilize the trace of Hessian response pyramids to identify candidate object types in the input images,subject the identified candidate object types to candidate feature processing to identify valid object types in the warehouse, andutilize navigational data based upon the valid object type identification.
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Accused Products
Abstract
An industrial vehicle is provided comprising a drive mechanism, a steering mechanism, a vehicle controller, a camera, and a navigation module. The camera is communicatively coupled to the navigation module, the vehicle controller is responsive to commands from the navigation module, and the drive mechanism and the steering mechanism are responsive to commands from the vehicle controller. The camera is configured to capture an input image of a warehouse ceiling comprising elongated skylights characterized by different rates of image intensity change along longitudinal and transverse axial directions, and ceiling lights characterized by a circularly symmetric rate of image intensity change. The navigation module is configured to distinguish between the ceiling lights and the skylights and send commands to the vehicle controller for localization, or to navigate the industrial vehicle through the warehouse based upon valid ceiling light identification, valid skylight identification, or both.
12 Citations
24 Claims
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1. A system comprising a vehicle camera, and a navigation module, wherein:
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the vehicle camera is communicatively coupled to the navigation module and is configured to capture input images of a warehouse; the navigation module is configured to distinguish between object types in the input images by executing machine readable instructions to create Gaussian scale space pyramids from the input images of the warehouse, build determinant of Hessian response pyramids from the Gaussian scale space pyramids, build trace of Hessian response pyramids from the Gaussian scale space pyramids, utilize the determinant of Hessian response pyramids to identify candidate object types in the input images, utilize the trace of Hessian response pyramids to identify candidate object types in the input images, subject the identified candidate object types to candidate feature processing to identify valid object types in the warehouse, and utilize navigational data based upon the valid object type identification. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A system comprising a vehicle camera, and a navigation module, wherein:
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the vehicle camera is communicatively coupled to the navigation module and is configured to capture input images of a ceiling in a warehouse; and the navigation module is configured to distinguish between object types in the input images by executing machine readable instructions to create Gaussian scale space pyramids from the input images of the warehouse-ceiling, build determinant of Hessian response pyramids from the Gaussian scale space pyramids, build trace of Hessian response pyramids from the Gaussian scale space pyramids, utilize the trace of Hessian response pyramids to identify candidate object types in the input images that are characterized by different rates of image intensity change along a plurality of axial directions, utilize the determinant of Hessian response pyramids to identify candidate object types in the input images that are characterized by a circularly symmetric rate of image intensity change, subject the identified candidate object types to candidate feature processing to identify valid object types in the warehouse, and utilize navigational data based upon the valid object type identification.
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24. A vehicle comprising a drive mechanism, a steering mechanism, a vehicle controller, a camera, and a navigation module, wherein:
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the camera is communicatively coupled to the navigation module and is configured to capture input images of a ceiling in a warehouse; the vehicle controller is responsive to commands from the navigation module; the drive mechanism and the steering mechanism are responsive to commands from the vehicle controller; and the navigation module is configured to distinguish between object types in the input images by executing machine readable instructions to create Gaussian scale space pyramids from the input images of the warehouse-ceiling, build determinant of Hessian response pyramids from the Gaussian scale space pyramids, build trace of Hessian response pyramids from the Gaussian scale space pyramids, utilize the trace of Hessian response pyramids to identify candidate object types in the input images that are characterized by different rates of image intensity change along a plurality of axial directions, utilize the determinant of Hessian response pyramids to identify candidate object types in the input images that are characterized by a circularly symmetric rate of image intensity change, subject the identified candidate object types to candidate feature processing to identify valid object types in the warehouse, and send commands to the vehicle controller to navigate the vehicle through the warehouse based upon the valid object type identification.
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Specification