公开(公告)号：US12062202B2

公开(公告)日：2024-08-13

申请号：US17485046

申请日：2021-09-24

Applicant: Argo AI, LLC

Inventor： Weizhao Shao ,  Ankit Kumar Jain ,  Xxx Xinjilefu ,  Gang Pan ,  Brendan Christopher Byrne

IPC: G06T7/70 ,  G01C21/30 ,  G06T7/50

CPC classification number: G06T7/70 ,  G01C21/30 ,  G06T7/50 ,  G06T2207/10028 ,  G06T2207/30252

Abstract: A system and method for performing visual localization is disclosed. In aspects, the system implements methods to generate a global point cloud, the global point cloud representing a plurality of point clouds. The global point cloud can be mapped to a prior map information to locate a position of an autonomous vehicle, the prior map information representing pre-built geographic maps. The position of the autonomous vehicle can be estimated based on applying sensor information obtained from sensors and software of the autonomous vehicle to the mapped global point cloud.

公开(公告)号：US12008777B2

公开(公告)日：2024-06-11

申请号：US17508681

申请日：2021-10-22

Applicant: ARGO AI, LLC

Inventor： Kunal Anil Desai ,  Xxx Xinjilefu ,  Gang Pan ,  Manu Sethi ,  Tao V. Fu

IPC: G06T7/579 ,  G01S17/894 ,  G01S17/931

CPC classification number: G06T7/579 ,  G01S17/894 ,  G01S17/931 ,  G06T2207/10028

Abstract: Disclosed herein are system and method embodiments to implement a validation of an SfM map. An embodiment operates by receiving a motion-generated map corresponding to a digital image, generating a first depth map, wherein the first depth map comprises depth information for one or more triangulated points located within the motion generated image. The embodiment further receives a light detection and ranging (lidar) generated point cloud including at least a portion of the one or more triangulated points, splats the lidar point cloud proximate to the portion of the one or more triangulated points and generates a second depth map for the portion and identifies an incorrect triangulated point, of the one or more triangulated points, based on comparing the first depth information to the second depth information. The incorrect triangulated points may be removed from the SfM map or marked with a low degree of confidence.

公开(公告)号：US12190541B2

公开(公告)日：2025-01-07

申请号：US18513247

申请日：2023-11-17

Applicant: Argo AI, LLC

Inventor： Philippe Babin ,  Kunal Anil Desai ,  Tao V. Fu ,  Gang Pan ,  Xxx Xinjilefu

IPC: G01S17/89 ,  B60W60/00 ,  G01S7/48 ,  G06T7/73

Abstract: Disclosed herein are system, method, and computer program product embodiments for automated autonomous vehicle pose validation. An embodiment operates by generating a range image from a point cloud solution comprising a pose estimate for an autonomous vehicle. The embodiment queries the range image for predicted ranges and predicted class labels corresponding to lidar beams projected into the range image. The embodiment generates a vector of features from the range image. The embodiment compares a plurality of values to the vector of features using a binary classifier. The embodiment validates the autonomous vehicle pose based on the comparison of the plurality of values to the vector of features using the binary classifier.

公开(公告)号：US11861865B2

公开(公告)日：2024-01-02

申请号：US17541094

申请日：2021-12-02

Applicant: Argo AI, LLC

Inventor： Philippe Babin ,  Kunal Anil Desai ,  Tao V. Fu ,  Gang Pan ,  Xxx Xinjilefu

IPC: G01S17/89 ,  G01S7/48 ,  B60W60/00 ,  G06T7/73

CPC classification number: G06T7/74 ,  B60W60/001 ,  G01S7/4808 ,  G01S17/89 ,  B60W2420/52 ,  G06T2207/10028 ,  G06T2207/30252

Abstract: Disclosed herein are system, method, and computer program product embodiments for automated autonomous vehicle pose validation. An embodiment operates by generating a range image from a point cloud solution comprising a pose estimate for an autonomous vehicle. The embodiment queries the range image for predicted ranges and predicted class labels corresponding to lidar beams projected into the range image. The embodiment generates a vector of features from the range image. The embodiment compares a plurality of values to the vector of features using a binary classifier. The embodiment validates the autonomous vehicle pose based on the comparison of the plurality of values to the vector of features using the binary classifier.

公开(公告)号：US20230128756A1

公开(公告)日：2023-04-27

申请号：US17508681

申请日：2021-10-22

Applicant: ARGO AI,LLC

Inventor： Kunal Anil DESAI ,  Xxx Xinjilefu ,  Gang Pan ,  Manu Sethi ,  Tao V. Fu

IPC: G06T7/579 ,  G01S17/894

Abstract: Disclosed herein are system and method embodiments to implement a validation of an SfM map. An embodiment operates by receiving a motion-generated map corresponding to a digital image, generating a first depth map, wherein the first depth map comprises depth information for one or more triangulated points located within the motion generated image. The embodiment further receives a light detection and ranging (lidar) generated point cloud including at least a portion of the one or more triangulated points, splats the lidar point cloud proximate to the portion of the one or more triangulated points and generates a second depth map for the portion and identifies an incorrect triangulated point, of the one or more triangulated points, based on comparing the first depth information to the second depth information. The incorrect triangulated points may be removed from the SfM map or marked with a low degree of confidence.