Unified Spatiotemporal Calibration of Monocular Cameras and Planar Lidars

Abstract

Monocular cameras and planar lidar sensors are complementary. While monocular visual odometry (VO) is a relatively low-drift method for measuring platform egomotion, it suffers from a scale ambiguity. A planar lidar scanner, in contrast, is able to provide precise distance information with known scale. In combination, a monocular camera-2D lidar pair can be used as a performance 3D scanner, at a much lower cost than existing 3D lidar units. However, for accurate scan acquisition, the two sensors must be spatially and temporally calibrated. In this paper, we extend recent work on a calibration technique based on Rényi’s quadratic entropy (RQE) to the unified spatiotemporal calibration of monocular cameras and 2D lidars. We present simulation results indicating that calibration errors of less than 5 mm, 0.1$^\circ$, and 0.15 ms in translation, rotation, and time delay, respectively, are readily achievable. Using real-world data, in the absence of reliable ground truth, we demonstrate high repeatability given sufficient platform motion. Unlike existing techniques, we are able to calibrate in arbitrary, target-free environments and without the need for overlapping sensor fields of view.