Programmable ROI variable density for high-resolution LiDAR using dual-axis scanning

The limitations of low resolution and computational efficiency remain critical in scanning-mirror LiDAR (SM-LiDAR) under complex scenarios. In this work, we propose a programmable region-of-interest (ROI) variable-density scanning method for prescribed spatial positions. Nonlinear phase correction and time-varying frequency modulation are used to regulate scanning density at arbitrary ROI positions. The results are grouped by physical meaning into ROI densification, scanning efficiency with angular resolution, and reconstruction accuracy. For ROI densification, the equivalent scanning lines within the ROI are increased by 5.46 times over conventional Lissajous scanning, and the ROI target-feature-point proportion reaches 5.12%. For scanning efficiency and angular resolution, unidirectional scanning is completed in approximately 370 μs, and the ROI angular resolution is improved from 0.1° for the RoboSense M1 Plus LiDAR to 0.057°, corresponding to an improvement of approximately 43%. For reconstruction accuracy, a minimum MAPE of 1.90% is achieved. These results support efficient high-resolution 3D perception for autonomous driving and robotic vision.