US 11,994,408 B2
Incremental map building using learnable features and descriptors
Jiexiong Tang, Stockholm (SE); Rares Andrei Ambrus, San Francisco, CA (US); Hanme Kim, San Jose, CA (US); Vitor Guizilini, Santa Clara, CA (US); Adrien David Gaidon, Mountain View, CA (US); Xipeng Wang, Ann Arbor, MI (US); Jeff Walls, Mountain View, CA (US); and Sudeep Pillai, Santa Clara, CA (US)
Assigned to TOYOTA RESEARCH INSTITUTE, INC., Los Altos, CA (US)
Filed by TOYOTA RESEARCH INSTITUTE, INC., Los Altos, CA (US)
Filed on Apr. 14, 2021, as Appl. No. 17/230,942.
Claims priority of provisional application 63/009,941, filed on Apr. 14, 2020.
Prior Publication US 2021/0318140 A1, Oct. 14, 2021
Int. Cl. G01C 21/00 (2006.01)
CPC G01C 21/3837 (2020.08) [G01C 21/3826 (2020.08); G01C 21/3896 (2020.08)] 17 Claims
OG exemplary drawing
 
1. A method for localization performed by a vehicle, comprising:
capturing, via one or more sensors integrated with the vehicle, a query image of a current environment of the vehicle, the query image being a two-dimensional (2D) image;
identifying a target image, from a plurality of images associated with a three-dimensional (3D) map of the current environment, comprising a first set of keypoints that match a second set of keypoints of the query image, each image of the plurality of images associated with a respective set of keypoints that are labelled via a keypoint model trained for 2D-to-3D keypoint matching;
determining a current location within the 3D map based on identifying the target image; and
autonomously or semi-autonomously navigating through the current environment based on determining the current location.