US 12,330,784 B2
Image space motion planning of an autonomous vehicle
Ryan David Kennedy, San Francisco, CA (US); Peter Benjamin Henry, San Francisco, CA (US); Hayk Martirosyan, San Francisco, CA (US); Jack Louis Zhu, San Mateo, CA (US); Abraham Galton Bachrach, Emerald Hills, CA (US); and Adam Parker Bry, Redwood City, CA (US)
Assigned to Skydio, Inc., San Mateo, CA (US)
Filed by Skydio, Inc., San Mateo, CA (US)
Filed on Sep. 8, 2023, as Appl. No. 18/463,826.
Application 17/513,138 is a division of application No. 16/789,176, filed on Feb. 12, 2020, granted, now 11,347,244, issued on May 31, 2022.
Application 18/463,826 is a continuation of application No. 18/162,193, filed on Jan. 31, 2023, granted, now 11,858,628.
Application 18/162,193 is a continuation of application No. 17/513,138, filed on Oct. 28, 2021, granted, now 11,592,844, issued on Feb. 28, 2023.
Application 16/789,176 is a continuation of application No. 15/671,743, filed on Aug. 8, 2017, granted, now 10,599,161, issued on Mar. 24, 2020.
Prior Publication US 2024/0228035 A1, Jul. 11, 2024
Int. Cl. G01C 21/34 (2006.01); B64C 39/02 (2023.01); B64U 10/14 (2023.01); G05D 1/00 (2006.01); G06T 7/246 (2017.01); G06T 7/277 (2017.01); G06T 7/593 (2017.01); G06T 17/05 (2011.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G08G 5/55 (2025.01); G08G 5/57 (2025.01); G08G 5/80 (2025.01); B64U 101/32 (2023.01)
CPC B64C 39/024 (2013.01) [B64U 10/14 (2023.01); G01C 21/3453 (2013.01); G05D 1/106 (2019.05); G06T 7/246 (2017.01); G06T 7/277 (2017.01); G06T 7/593 (2017.01); G06T 17/05 (2013.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G08G 5/55 (2025.01); G08G 5/57 (2025.01); G08G 5/80 (2025.01); B64U 2101/32 (2023.01); B64U 2201/10 (2023.01); B64U 2201/20 (2023.01); G06T 2207/10021 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30188 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30252 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
processing an image to generate or modify a cost function map,
wherein the cost function map associates a cost to at least one region of multiple regions of the image,
wherein the cost comprises a value indicative of a measure of risk associated with navigating in an area of the physical environment corresponding to the at least one region of the image; and
causing a vehicle to autonomously maneuver through the physical environment using the cost function map.