Expansion of the Field of View for 3-D Cameras Based on Servo Mirror

This study introduces a servo-mirror 3-D camera field expander that overcomes the limitations of fixed-mirror systems through dynamically adjustable mirror configurations. The proposed system enables flexible field-of-view (FOV) expansion for 3-D cameras while maintaining high accuracy and operational efficiency. Our technical contributions include: 1) a servo-mirror-based FOV expansion system that dynamically adjusts mirror position and orientation to enable significant FOV enhancement; 2) a vision-based auto-calibration method that eliminates mechanical encoder dependency while enabling real-time reflected point cloud correction; and 3) a reflected point cloud segmentation algorithm for rapid nonreflective region filtering. Through kinematic analysis, we establish the sensor’s operational workspace using voxel-based 3-D heatmaps, quantitatively characterizing its effective measurement range. Experimental results demonstrate that the FOV expander achieves accuracy comparable to the native camera (with measurement errors of less than 0.2 mm and 0.5° in dimensional and angular measurements, respectively) while completing full 3-D reconstruction within 4 min. The FOV expander represents a significant advancement in adaptable 3-D sensing, particularly for applications requiring both wide FOV coverage and high accuracy.