Crowd-sensed point cloud map
First Claim
1. A method for controlling an autonomous vehicle, comprising:
- receiving sensor data from a sensor of the vehicle;
determining a three dimensional point cloud map segment from the sensor data;
determining a vehicle pose associated with the three-dimensional point cloud map segment;
determining a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference;
aligning the three dimensional point cloud map segment with another three dimensional point cloud map segment associated with the other vehicle pose based on the pose difference; and
controlling the vehicle based on the aligned three dimensional point cloud map segments.
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Accused Products
Abstract
Systems and method are provided for controlling an autonomous vehicle. In one embodiment, a method includes: receiving sensor data from a sensor of the vehicle; determining a three dimensional point cloud map segment from the sensor data; determining a vehicle pose associated with the three-dimensional point cloud map segment; determining a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference; aligning the three dimensional point cloud map segment with another three dimensional point cloud map segment associated with the other vehicle pose based on the pose difference; and controlling the vehicle based on the aligned three dimensional point cloud map segments.
10 Citations
20 Claims
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1. A method for controlling an autonomous vehicle, comprising:
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receiving sensor data from a sensor of the vehicle; determining a three dimensional point cloud map segment from the sensor data; determining a vehicle pose associated with the three-dimensional point cloud map segment; determining a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference; aligning the three dimensional point cloud map segment with another three dimensional point cloud map segment associated with the other vehicle pose based on the pose difference; and controlling the vehicle based on the aligned three dimensional point cloud map segments. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-implemented system for controlling an autonomous vehicle, comprising:
a non-transitory computer readable medium comprising; a map segment generation module configured to receive sensor data from a sensor of the vehicle, and determine a three dimensional point cloud map segment from the sensor data; a pose determination module configured to determine a vehicle pose associated with the three-dimensional map segment; a pose difference determination module configured to determine a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference; an alignment module configured to align the three dimensional point cloud map segment with another three dimensional map segment associated with the other vehicle pose based on the pose difference; and a control module configured to control the vehicle based on the aligned three dimensional point cloud map segments. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
Specification