Shanghaitech University

Yunhao Hu

Yajun Ha

A fast and energy-efficient K-nearest neighbors search accelerator for a large-scale point cloud is provided. A nearest sub-voxel-selection (NSVS) framework that performs search based on a double-segmentation-voxel-structure (DSVS) search structure is constructed, and a K-nearest neighbors search algorithm for a large-scale point cloud map is implemented on a field programmable gate array (FPGA). The K-nearest neighbors search accelerator is configured for constructing the DSVS search structure, and searching for K-nearest neighbors based on the DSVS search structure. An experimental result on a KITTI dataset shows that the K-nearest neighbors search accelerator has a search speed 9.1 times faster than a state-of-the-art FPGA implementation. In addition, the K-nearest neighbors search accelerator also achieves an optimal energy efficiency, and the optimal energy efficiency is 11.5 times and 13.5 times higher than state-of-the-art FPGA and GPU implementations respectively.

Growing community of inventors

Shanghai, China

Yunhao Hu