US 12,223,677 B1
Map-anchored object detection
Louis Foucard, San Francisco, CA (US)
Assigned to AURORA OPERATIONS, INC., Pittsburgh, PA (US)
Filed by Aurora Operations, Inc., Pittsburgh, PA (US)
Filed on Jul. 18, 2023, as Appl. No. 18/354,415.
Int. Cl. G06T 7/73 (2017.01); B60W 60/00 (2020.01)
CPC G06T 7/74 (2017.01) [B60W 60/001 (2020.02); B60W 2420/00 (2013.01); B60W 2554/00 (2020.02); B60W 2556/00 (2020.02); G06T 2207/20081 (2013.01); G06T 2207/30204 (2013.01); G06T 2207/30256 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
(a) obtaining sensor data descriptive of an environment of an autonomous vehicle;
(b) obtaining a plurality of travel way markers from map data descriptive of the environment;
(c) determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and an object in the environment; and
(d) generating, using the machine-learned object detection model, an offset with respect to the one or more travel way markers of a spatial region of the environment associated with the object;
wherein (c) comprises:
inputting the travel way markers and the sensor data to the machine-learned object detection model; and
obtaining object data from the machine-learned object detection model at projected locations of the travel way markers in a reference frame of the sensor data, wherein the object data indicates that the object is likely to be present at a projected location of the one or more travel way markers.