Automatic Multi-Sensor Extrinsic Calibration For Mobile Robots

In order to fuse measurements from multiple sensors mounted on a mobile robot, it is needed to express them in a common reference system through their relative spatial transformations. In this letter, we present a method to estimate the full 6-DoF extrinsic calibration parameters of multiple heterogeneous sensors (Lidars, depth, and RGB cameras) suitable for automatic execution on a mobile robot. Our method computes the two-dimensional calibration parameters (
x
,
y
, and yaw) through a motion-based approach, whereas for the remaining three parameters (
z
, pitch, and roll), it requires the observation of the ground plane for a short period of time. What set this proposal apart from others is that all calibration parameters are initialized in closed form, and the scale ambiguity inherent to motion estimation from a monocular camera is explicitly handled, enabling the combination of these sensors and metric ones (Lidars, stereo rigs, etc.) within the same optimization framework. We provide a formal definition of the problem, as well as of the contributed method, for which a C++ implementation has been made publicly available. The suitability of the method has been assessed in simulation and with real data from indoor and outdoor scenarios. Finally, improvements over state-of-the-art motion-based calibration proposals are shown through experimental evaluation.