Autonomous vehicle localization using passive image data
First Claim
Patent Images
1. A method for performing localization for a vehicle in motion, the method being implemented by one or more processors and comprising:
- obtaining a set of sensor data captured by the vehicle at a given instance as the vehicle traverses a given area of a road network, the sensor data including passive image data;
selecting a feature from a known feature set for the given area of the road network based on one or more conditions that affect an appearance of individual features of the known feature set;
matching an image subset of the passive image data to the feature from the known feature set for the given area of the road network; and
determining a location of the vehicle within the given area based on reference location information previously associated with the known feature set.
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Abstract
A system to use submaps to control operation of a vehicle is disclosed. A storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps.
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Citations
21 Claims
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1. A method for performing localization for a vehicle in motion, the method being implemented by one or more processors and comprising:
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obtaining a set of sensor data captured by the vehicle at a given instance as the vehicle traverses a given area of a road network, the sensor data including passive image data; selecting a feature from a known feature set for the given area of the road network based on one or more conditions that affect an appearance of individual features of the known feature set; matching an image subset of the passive image data to the feature from the known feature set for the given area of the road network; and determining a location of the vehicle within the given area based on reference location information previously associated with the known feature set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method for performing localization for a vehicle in motion, the method being implemented by one or more processors and comprising:
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obtaining a set of sensor data captured by the vehicle at a given instance as the vehicle traverses a given area of a road network, the sensor data including passive image data; matching an image subset of the passive image data to a feature from a known feature set for the given area of the road network, wherein matching the image subset includes implementing one or more rules based on a presence of one or more conditions that affect an appearance of individual features of the known feature set; and determining a location of the vehicle within the given area based on reference location information previously associated with the known feature set. - View Dependent Claims (16, 17)
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18. A computer system comprising:
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a memory to store a set of instructions; one or more processors to use the set of instructions to; obtain a set of sensor data captured by a vehicle at a given instance as the vehicle traverses a given area of a road network, the sensor data including passive image data; select a feature from a known feature set for the given area of the road network based on one or more conditions that affect an appearance of individual features of the known feature set; match an image subset of the passive image data to the feature from the known feature set for the given area of the road network; and determines a location of the vehicle within the given area based on reference location information previously associated with the known feature set. - View Dependent Claims (19, 20)
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21. A computer system comprising:
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a memory to store a set of instructions; one or more processors to use the set of instructions to; obtain a set of sensor data captured by a vehicle at a given instance as the vehicle traverses a given area of a road network, the sensor data including passive image data; match an image subset of the passive image data to the feature from a known feature set for the given area of the road network; determine a location of the vehicle within the given area based on reference location information previously associated with the known feature set; determine a submap from a collection of submaps that corresponds to the area of the road network where the vehicle is located, wherein the submap includes one or more data layers which include the known feature set, wherein the one or more data layers provide a three-dimensional pointcloud, in which individual points of the pointcloud are associated with imagelets representing one or more features of the known feature set; and select a set of points with associated imagelets from a larger number of points of the pointcloud with associated imagelets based on information associated with individual points in the larger number of points, the associated imagelets of the selected set of points corresponding to the known feature set, and wherein the information associated with individual points in the larger number of points include at least one of a semantic label, geometric information and/or contextual information.
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Specification