US 12,093,824 B2
Distance to obstacle detection in autonomous machine applications
Yilin Yang, Santa Clara, CA (US); Bala Siva Sashank Jujjavarapu, Sunnyvale, CA (US); Pekka Janis, Uusimaa (FI); Zhaoting Ye, Santa Clara, CA (US); Sangmin Oh, San Jose, CA (US); Minwoo Park, Saratoga, CA (US); Daniel Herrera Castro, Uusimaa (FI); Tommi Koivisto, Uusimaa (FI); and David Nister, Bellevue, WA (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Jun. 28, 2023, as Appl. No. 18/343,291.
Application 18/343,291 is a continuation of application No. 17/723,195, filed on Apr. 18, 2022, granted, now 11,790,230.
Application 17/723,195 is a continuation of application No. 17/449,310, filed on Sep. 29, 2021, granted, now 11,769,052.
Application 17/449,310 is a continuation of application No. 16/813,306, filed on Mar. 9, 2020, granted, now 11,170,299, issued on Nov. 9, 2021.
Application 16/813,306 is a continuation in part of application No. 16/728,595, filed on Dec. 27, 2019, granted, now 11,308,338, issued on Apr. 19, 2022.
Claims priority of provisional application 62/786,188, filed on Dec. 28, 2018.
Prior Publication US 2024/0135173 A1, Apr. 25, 2024
Prior Publication US 2024/0232616 A9, Jul. 11, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06K 9/00 (2022.01); B60W 30/14 (2006.01); B60W 60/00 (2020.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06V 10/762 (2022.01); G06V 20/56 (2022.01)
CPC G06N 3/08 (2013.01) [B60W 30/14 (2013.01); B60W 60/0011 (2020.02); G06F 18/2155 (2023.01); G06V 10/763 (2022.01); G06V 20/56 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
determining, using one or more machine learning models and based at least on sensor data obtained using one or more sensors of a vehicle, one or more depth values corresponding to one or more bounding shapes associated with an object;
determining, based at least on the one or more depth values, an associated depth value for the object; and
causing the vehicle to perform one or more operations based at least on the associated depth value for the object.