Variable-density scanning strategy and ROI density analysis for high-precision MEMS LiDAR

In MEMS LiDAR for industrial robotics, conventional Lissajous scanning suffers from fixed-density point clouds, causing sparse resolution in regions of interest (ROI) and redundancy in non-critical areas. To address this issue we propose a phase modulation (PM) strategy that enables dynamic adaptive variable-density ROI scanning using a single resonant mirror. Three types of variable density modulation achieve ROI switching within the nine-grid region. Kernel density estimation quantified scanning density, revealing a peak of 10.3596 in ROIs. An innovative minimum angular separation method is also proposed for the precise assessment of angular separation within the ROI. Compared to the conventional approach, this method decreases angular separation by up to 68.26% and increases scanning density by up to 75.52%. The experimental results align with theoretical predictions, showing seamless and interference-free transitions between ROI modes. The PM strategy achieves localized density enhancement without global redundancy and avoids the need for multiple mirrors, thus contributing to both LiDAR system integration and accuracy improvement.