US 12,093,348 B2
Systems and methods for bayesian likelihood estimation of fused objects
Sowmya Gade, Redwood City, CA (US); Gary Fay, Hermosa Beach, CA (US); and Aziz Umit Batur, Torrance, CA (US)
Assigned to Rivian IP Holdings, LLC, Irvine, CA (US)
Filed by Rivian IP Holdings, LLC, Plymouth, MI (US)
Filed on Nov. 24, 2021, as Appl. No. 17/534,498.
Claims priority of provisional application 63/239,123, filed on Aug. 31, 2021.
Prior Publication US 2023/0061682 A1, Mar. 2, 2023
Int. Cl. G06F 18/25 (2023.01); B60W 50/00 (2006.01); G06V 20/56 (2022.01); B60W 10/04 (2006.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); B60W 10/22 (2006.01)
CPC G06F 18/251 (2023.01) [B60W 50/0098 (2013.01); G06V 20/56 (2022.01); B60W 10/04 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); B60W 10/22 (2013.01); B60W 2050/0052 (2013.01); B60W 2420/403 (2013.01); B60W 2420/408 (2024.01); B60W 2556/35 (2020.02); B60W 2710/18 (2013.01); B60W 2710/20 (2013.01); B60W 2710/22 (2013.01); B60W 2720/106 (2013.01); B60W 2720/125 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A sensor fusion method, comprising:
receiving a plurality of object detection measurements from a plurality of sensors, each of the plurality of object detection measurements being associated with a respective one of a plurality of potential object detection tracks, each of the plurality of sensors having a different field of view based on a corresponding location on a vehicle;
receiving a plurality of sensor confidence values associated with the plurality of sensors;
determining a track confidence value for each of the plurality of potential object detection tracks based on the plurality of object detection measurements and the plurality of sensor confidence values; and
fusing at least two of the plurality of potential object detection tracks corresponding to different fields of view into a true object detection for controlling at least a portion of the vehicle based at least in part on the track confidence value of each of the at least two of the plurality of potential object detection tracks meeting a predetermined detection threshold.