Automatic localization geometry detection

1. A method for automatic generation of a localization geometry, the method comprising:

receiving point cloud data collected by a distance sensor and describing a vicinity of a pathway;

reducing, by a processor, the point cloud data to a predetermined volume with respect to the pathway;

projecting, by the processor, the point cloud data to a two-dimensional plane including at least one pixel formation;

defining, by the processor, a volumetric grid according to the at least one pixel formation;

determining, by the processor, a voxel occupancy for each of a plurality of voxels forming the volumetric grid; and

generating, by the processor, the localization geometry according to the voxel occupancy.

2. The method of claim 1 , wherein reducing the point cloud data to the predetermined volume includes:

determining a first horizontal border of the pathway;

determining a second horizontal border of the pathway; and

filtering data of the point cloud data to remove data between the first horizontal border and the second horizontal border.

3. The method of claim 1 , wherein reducing the point cloud data to the predetermined volume includes:

determining a first vertical border in a plane parallel to the pathway;

determining a second vertical border in a plane parallel to the pathway; and

filtering data of the point cloud data to remove data between the first vertical border and the second vertical border.

4. The method of claim 3 , wherein the first vertical border corresponds to a height of a collection vehicle for the point cloud data.

5. The method of claim 1 , wherein reducing the point cloud data to the predetermined volume includes:

determining an outer border for the pathway; and

filtering data of the point cloud data to remove data farther from the pathway than the outer border.

6. The method of claim 1 , further comprising:

defining a plurality of chunks of the pathway, each chunk having a predetermined length, wherein at least one object described in the point cloud data extends across multiple chunks.

7. The method of claim 1 , wherein the two-dimensional plane includes a two-dimensional grid having cells of a predetermined area, the method further comprising:

filtering data in cells having less than a predetermined number of data points.

8. The method of claim 1 , further comprising:

identifying the at least one pixel formation from the two-dimensional plane; and

generating the volumetric grid from the at least one pixel formation.

9. The method of claim 1 , further comprising:

defining a primary direction in the volumetric grid;

defining a secondary direction in the volumetric grid;

defining a tertiary direction in the volumetric grid; and

storing occupancy data for the volumetric data according to a sequence of the primary direction, the secondary direction, and the tertiary direction.

10. The method of claim 1 , further comprising:

transforming the volumetric grid to the localization geometry according to a transformation matrix or a transformation quaternion.

11. The method of claim 10 , wherein the volumetric grid is in local coordinates and the localization geometry is in geodetic coordinates.

12. The method of claim 1 , wherein subsequent point cloud data is compared to the localization geometry in order to determine a geographic position of a mobile device.

13. An apparatus for automatic generation of a localization geometry of a roadway, the apparatus comprising:

a communication interface configured to receive point cloud data collected by a distance sensor and describing a vicinity of a roadway; and

a controller configured to reduce the point cloud data to a predetermined volume with respect to the roadway, project the point cloud data to a two-dimensional plane including at least one pixel formation, and determine a voxel occupancy for each of a plurality of voxels corresponding to the at least one pixel formation,

wherein the voxel occupancy for a grid defines the localization geometry of the roadway.

14. The apparatus of claim 13 , wherein the controller reduces the point cloud data according to removal of data between borders associated with the roadway.

15. The apparatus of claim 13 , wherein the controller reduces the point cloud data according to removal of data between a first vertical border in a plane parallel to the roadway and a second vertical border in a plane parallel to the roadway.

16. The apparatus of claim 13 , wherein the controller reduces the point cloud data according to removal of data farther from the roadway than an outer border for the roadway.

17. The apparatus of claim 13 , wherein the controller defines a plurality of chunks of the roadway, each chunk having a predetermined length, wherein at least one object described in the point cloud data extends across multiple chunks.

18. The apparatus of claim 13 , further comprising:

a memory comprising occupancy data for the grid arranged in an order that spans multiple dimensions of the grid.

19. The apparatus of claim 13 , wherein the controller transforms the grid to the localization geometry according to a transformation matrix or a transformation quaternion.

20. A system for automatic generation of a localization geometry of a roadway, the system comprising:

a distance sensor configured to receive point cloud data collected by a distance sensor and describing a vicinity of a roadway; and

a controller configured to reduce the point cloud data to a predetermined volume with respect to the roadway and project the point cloud data to a two-dimensional plane including at least one pixel formation,

wherein the localization geometry includes a volumetric grid is populated according to a voxel occupancy value for at least one pixel formation.