US 11,928,585 B2
Neural network architecture for small LIDAR processing networks for slope estimation and ground plane segmentation
Christopher Serrano, Whittier, CA (US); Michael A. Warren, Northridge, CA (US); and Aleksey Nogin, Fresno, CA (US)
Assigned to HRL LABORATORIES, LLC, Malibu, CA (US)
Filed by HRL Laboratories, LLC, Malibu, CA (US)
Filed on Nov. 17, 2020, as Appl. No. 16/950,803.
Claims priority of provisional application 62/984,676, filed on Mar. 3, 2020.
Claims priority of provisional application 62/984,693, filed on Mar. 3, 2020.
Prior Publication US 2021/0278854 A1, Sep. 9, 2021
Int. Cl. G06N 3/08 (2023.01); B60W 60/00 (2020.01); G05D 1/00 (2006.01); G05D 1/02 (2020.01); G06F 7/544 (2006.01)
CPC G06N 3/08 (2013.01) [G05D 1/0221 (2013.01); G05D 1/0276 (2013.01); B60W 60/001 (2020.02); B60W 2556/45 (2020.02); G06F 7/544 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A system for operating an autonomous platform in an environment using information extracted from point cloud data in the environment, the system comprising:
a sensor generating point cloud data; and
one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of:
training a neural network model with imageless data, the imageless data being exclusively the point cloud data, comprising:
using a parallelizable k-nearest neighbor sorting algorithm, providing a patch of points sampled from the point cloud data as input to the neural network model, wherein the patch of points has a central point;
transforming the patch of points from Euclidean coordinates in a Euclidean space to spherical coordinates; and
generating normalized points by projection onto the unit sphere;
estimating a polar angle of a surface normal of the normalized points in the spherical coordinates;
utilizing the trained neural network model on the autonomous platform; and
using the estimate of the polar angle of the surface normal to guide operation of the autonomous platform within the environment.