Neural network architecture for small lidar processing networks for slope estimation and ground plane segmentation

A computer implemented method for operating an autonomous platform in an environment using information extracted from point cloud data in the environment, the method comprising an act of:

• causing one or more processors to execute instructions encoded on one or more associated memories, each associated memory being a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of:
• training a neural network model, 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 has a central point;
• transforming the points from Euclidean coordinates in a Euclidean space to spherical coordinates;
• and
• estimating a polar angle of a surface normal of the point cloud data 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.

A computer program product for operating an autonomous platform in an environment using information extracted from point cloud data in the environment, the computer program product comprising:

• computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of:
• training a neural network model, 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 has a central point;
• transforming the points from Euclidean coordinates in a Euclidean space to spherical coordinates;
• and
• estimating a polar angle of a surface normal of the point cloud data 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.