Wide-Range Joint Calibration Method of 2D-3D Sensors for Robot Navigation

Robotic navigation tasks require multi-dimensional sensors collaboration for environmental perception, where data fusion between camera and lidar plays a critical role in 2D-3D data fusion. However, the reliability of current 2D-3D sensors fusion approaches is limited by the accuracy, efficiency, and working range of joint sensors calibration. To address the challenges posed by the complexity and wide-range requirements of 2D-3D sensors calibration, this paper analyzes the characteristics of 2D and 3D data and proposes a novel multi-feature calibration target. This target integrates both checkerboard patterns and spherical markers, levesraging the camera’s sensitivity to planar features and the lidar’s ability to perceive spatial structures, thus enabling high-precision feature extraction for both sensors modalities. In addition, spatial alignment between the measurement domains of the two sensors is performed to achieve high-precision calibration of structural parameters across the entire measurement range. Experimental results demonstrate that the proposed joint calibration method achieves high accuracy and provides a reliable calibration foundation for robotic navigation and other 2D-3D sensors fusion tasks.