公开(公告)号：US20250060464A1

公开(公告)日：2025-02-20

申请号：US18898214

申请日：2024-09-26

Applicant: Aurora Operations, Inc.

Inventor： Hatem Alismail

IPC: G01S7/497 ,  G01S7/481 ,  G01S17/931

Abstract: Lidar intensity calibration from multi-beam lidar sensors uses calibration panels with known reflectance. The intensity response curves of each lidar beam are learned and modeled as a function of the known reflectivity, the transmission power level, and the range. Contrary to the lidar equation, characterization of multi-beam lidar scanners commonly used for autonomous driving applications reveals that intensity does not fall-off according to the theoretically expected inverse range-squared. Instead, a maximum intensity response is attained at a specific range (focal distance). While the focal distance varies across beams, it is independent of the transmission power. Outside of the focal distance, range intensity exhibits a sharp fall off. The intensity response curve of the lidar is well-approximated by a parametric form. Learned splines as functions of range and power level determine the most likely mapping from raw data to surface reflectance along with a measure of uncertainty.

公开(公告)号：US12298404B2

公开(公告)日：2025-05-13

申请号：US18520416

申请日：2023-11-27

Applicant: Aurora Operations, Inc.

Inventor： Peter Hansen ,  Hatem Alismail

IPC: G01S17/89 ,  G01S7/48 ,  G01S17/08 ,  G01S17/88 ,  G01S17/894 ,  G01S17/931 ,  G05D1/00 ,  G06T7/73

Abstract: A system for determining a pose of a vehicle and building maps from vehicle priors processes received ground intensity LIDAR data including intensity data for points believed to be on the ground and height information to form ground intensity LIDAR (GIL) images including pixels in 2D coordinates where each pixel contains an intensity value, a height value, and x- and y-gradients of intensity and height. The GIL images are formed by filtering aggregated ground intensity LIDAR data falling into a same spatial bin on the ground and using a registration algorithm to align two GIL images relative to one another by estimating a 6-degree-of-freedom pose with associated uncertainty that minimizes error between the two GIL images. The aligned GIL images are provided as a pose estimate to a localizer. The system may provide online localization and pose estimation, prior building, and prior to prior alignment pose estimation using image-based techniques.

公开(公告)号：US12135395B2

公开(公告)日：2024-11-05

申请号：US17247497

申请日：2020-12-14

Applicant: Aurora Operations, Inc.

Inventor： Hatem Alismail

IPC: G01S7/497 ,  G01S7/481 ,  G01S17/931

Abstract: Lidar intensity calibration from multi-beam lidar sensors uses calibration panels with known reflectance. The intensity response curves of each lidar beam are learned and modeled as a function of the known reflectivity, the transmission power level, and the distance. Contrary to the lidar equation, characterization of multi-beam lidar scanners commonly used for autonomous driving applications reveals that intensity does not fall-off according to the theoretically expected inverse distance-squared. Instead, a maximum intensity response is attained at a specific distance (focal distance). While the focal distance varies across beams, it is independent of the transmission power. Outside of the focal distance, distance intensity exhibits a sharp fall off. The intensity response curve of the lidar is well-approximated by a parametric form. Learned splines as functions of distance and power level determine the most likely mapping from raw data to surface reflectance along with a measure of uncertainty.