NORMAL DISTRIBUTIONS TRANSFORM (NDT) METHOD FOR LIDAR POINT CLOUD LOCALIZATION IN UNMANNED DRIVING

    公开(公告)号:US20230192123A1

    公开(公告)日:2023-06-22

    申请号:US17802148

    申请日:2021-09-22

    CPC classification number: B60W60/001 B60W2420/52 B60W2554/4049

    Abstract: A normal distributions transform (NDT) method for LiDAR point cloud localization in unmanned driving is provided. The method proposes a non-recursive, memory-efficient data structure occupation-aware-voxel-structure (OAVS), which speeds up each search operation. Compared with a tree-based structure, the proposed data structure OAVS is easy to parallelize and consumes only about 1/10 of memory. Based on the data structure OAVS, the method proposes a semantic-assisted OAVS-based (SEO)-NDT algorithm, which significantly reduces the number of search operations, redefines a parameter affecting the number of search operations, and removes a redundant search operation. In addition, the method proposes a streaming field-programmable gate array (FPGA) accelerator architecture, which further improves the real-time and energy-saving performance of the SEO-NDT algorithm. The method meets the real-time and high-precision requirements of smart vehicles for three-dimensional (3D) lidar localization.

    RIPPLE PUSH METHOD FOR GRAPH CUT
    2.
    发明公开

    公开(公告)号:US20230195793A1

    公开(公告)日:2023-06-22

    申请号:US17799278

    申请日:2021-09-22

    CPC classification number: G06F16/9024

    Abstract: A ripple push method for a graph cut includes: obtaining an excess flow ef(v) of a current node v; traversing four edges connecting the current node v in top, bottom, left and right directions, and determining whether each of the four edges is a pushable edge; calculating, according to different weight functions, a maximum push value of each of the four edges by efw=ef(v)*W, where W denotes a weight function; and traversing the four edges, recording a pushable flow of each of the four edges, and pushing out a calculated flow. The ripple push method explores different push weight functions, and significantly improves the actual parallelism of the push-relabel algorithm.

    DISORDERED PARALLEL MAXIMUM FLOW/MINIMUM CUT METHOD IMPLEMENTED BY ENERGY-EFFICIENT FIELD-PROGRAMMABLE GATE ARRAY (FPGA)

    公开(公告)号:US20240273273A1

    公开(公告)日:2024-08-15

    申请号:US18401731

    申请日:2024-01-02

    CPC classification number: G06F30/347 G06F30/392 G06F2111/10 G06F2115/10

    Abstract: A disordered parallel maximum flow/minimum cut method implemented by an energy-efficient field-programmable gate array (FPGA) folds a single-layer large two-dimensional grid graph into a multi-layer small grid graph. The method enables a folding grid architecture to store and process a grid graph that is much larger than a processor array in size. The folding grid architecture endows a two-dimensional processor array with a degree of freedom in a vertical direction, such that the two-dimensional processor array can leverage a potential for parallel performance of the folding grid architecture based on the degree of freedom in the vertical direction. The folding grid architecture enables a small-sized processor array to have an ability to process a grid graph that is much larger than the small-sized processor array in size. In addition, based on axial symmetry of folding, the folding grid architecture can greatly reduce cross-boundary transmission of data in the processor array.

Patent Agency Ranking