Li T Yu

US Patent:

20210158546, May 27, 2021

Filed:

Nov 22, 2019

Appl. No.:

16/692956

Inventors:

- Sunnyvale CA, US
Shiyu Song - Sunnyvale CA, US
Li Yu - Sunnyvale CA, US
Wendong Ding - Sunnyvale CA, US
Pengfei Yuan - Sunnyvale CA, US

International Classification:

G06T 7/33
G06T 7/73
G05D 1/00
G01S 19/45
G01S 17/89

Abstract:

In one embodiment, a system and method for point cloud registration of LIDAR poses of an autonomous driving vehicle (ADV) is disclosed. The method selects poses of the point clouds that possess higher confidence level during the data capture phase as fixed anchor poses. The fixed anchor points are used to estimate and optimize the poses of non-anchor poses during point cloud registration. The method may partition the points clouds into blocks to perform the ICP algorithm for each block in parallel by minimizing the cost function of the bundle adjustment equation updated with a regularity term. The regularity term may measure the difference between current estimates of the poses and previous or the initial estimates. The method may also minimize the bundle adjustment equation updated with a regularity term when solving the pose graph problem to merge the optimized poses from the blocks to make connections between the blocks.

US Patent:

20210158547, May 27, 2021

Filed:

Nov 22, 2019

Appl. No.:

16/692960

Inventors:

- Sunnyvale CA, US
SHIYU SONG - Sunnyvale CA, US
LI YU - Sunnyvale CA, US
WENDONG DING - Sunnyvale CA, US
PENGFEI YUAN - Sunnyvale CA, US

International Classification:

G06T 7/33
G06T 7/73
G01S 17/42
G01S 17/931
G01S 7/48

Abstract:

In one embodiment, a system and method for partitioning a region for point cloud registration of LIDAR poses of an autonomous driving vehicle (ADV) using a regional iterative closest point (ICP) algorithm is disclosed. The method determines the frame pair size of one or more pairs of related LIDAR poses of a region of an HD map to be constructed. If the frame pair size is greater than a threshold, the region is further divided into multiple clusters. The method may perform the ICP algorithm for each cluster. Inside a cluster, the ICP algorithm focuses on a partial subset of the decision variables and assumes the rest of the decision variables are fixed. To construct the HD map, the method may determine if the results of the ICP algorithms from the clusters converge. If the solutions converge, a solution to the point cloud registration for the region is found.