US 11,983,007 B2
Machine learning network based carriage control apparatus for maintenance striping
Douglas D. Dolinar, Doylestown, PA (US); William R. Haller, Bethlehem, PA (US); Charles R. Drazba, Conshohocken, PA (US); Matt W. Smith, Towanda, PA (US); Kyle J. Leonard, Philadelphia, PA (US); and Eric M. Stahl, Conshohocken, PA (US)
Assigned to LIMNTECH LLC, Souderton, PA (US)
Filed by LimnTech LLC, Souderton, PA (US)
Filed on Apr. 14, 2021, as Appl. No. 17/230,639.
Claims priority of provisional application 63/010,876, filed on Apr. 16, 2020.
Prior Publication US 2021/0326606 A1, Oct. 21, 2021
Int. Cl. G05D 1/00 (2006.01); G01S 17/87 (2020.01); G01S 17/89 (2020.01); G06N 3/08 (2023.01); G06V 10/98 (2022.01); G06V 20/56 (2022.01)
CPC G05D 1/0088 (2013.01) [G01S 17/87 (2013.01); G01S 17/89 (2013.01); G05D 1/0221 (2013.01); G06N 3/08 (2013.01); G06V 10/98 (2022.01); G06V 20/588 (2022.01); G06V 2201/07 (2022.01)] 15 Claims
OG exemplary drawing
 
1. A control system for positioning a marker over a pre-existing roadway surface mark, the control system comprising:
an imager having a field of view for imaging the roadway surface mark;
a sensor for determining the lateral location of the marker;
a computer responsive to the imager and to the sensor and programmatically configured to (a) process the image using a machine learning network and (b) produce an error signal based upon the lateral location difference between the processed image of the pre-existing roadway surface mark and the marker; and
an actuator attached to the marker and responsive to the error signal for positioning the marker over the pre-existing roadway mark;
wherein the machine learning network is a supervised machine learning network system configured to process illumination conditions of the roadway surface consisting of: shadows, color changes of the roadway surface, intersections, imager field of view variations, blending of the roadway mark into the roadway surface, and background clutter and noise.