Enhancing Point Cloud Density using MEMS Mirror-based Focusing for LiDAR Systems

Author:

Li Wen Jung1ORCID,YANG Donghai1,CHEN Meng,YU Xiaodong,CHEN Qingjiu1,ZHANG Guanglie2

Affiliation:

1. City University of Hong Kong

2. City University of Hong Kong; City University of Hong Kong Shenzhen Research Institute (CityUSRI)

Abstract

Abstract

LiDAR has become a prominent technology in 3D sensing due to its reliable distance detection. However, the sparse point cloud data it produces, particularly during long-range scanning, poses challenges for data processing. To overcome this, we developed a novel LiDAR system with a focusing functionality to improve point cloud density when scanning distance objects. The system, which comprises a MEMS mirror-based LiDAR and a CMOS camera, leverages the adjustable light beam steering of the MEMS mirror to dynamically alter the laser beam angle according to the target size, thereby enhancing the point cloud density for long-range targets. The integrated camera and image recognition technology facilitate automatic target detection, enabling dynamic control of the MEMS mirrors for focusing. Experimental results showed a significant increase in effective returns on the target from 18 to 93 after focusing at a distance of 30 meters, improving vertical resolution by 83.4%. Scanning of long-range targets also demonstrated a substantial enhancement in point cloud density and resolution.

Publisher

Springer Science and Business Media LLC

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