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Offline GNSS/Camera Extrinsic Calibration Using RTK and Fiducials

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Accurate robotic state estimation often requires precise knowledge of inter-sensor offsets. In this letter we present a solution for inter-sensor calibration of systems that employ a combination of GNSS and… Click to show full abstract

Accurate robotic state estimation often requires precise knowledge of inter-sensor offsets. In this letter we present a solution for inter-sensor calibration of systems that employ a combination of GNSS and visual-inertial sensors. RTK-GNSS and fiducial measurements are utilized to produce highly precise estimates. We present an offline batch estimation approach that utilizes a continuous-time spline on the Lie group SE(3). This approach simultaneously estimates the vehicle trajectory and sensor spatio-temporal offsets by choosing optimal spline control points and calibration parameters to solve a maximum likelihood estimation problem. Our calibration method is validated in both simulation and hardware, with comparison to an online extended Kalman filter. Hardware experiments are conducted in both a motion capture environment and outdoors. Results show that our method outperforms online methods and approaches millimeter-level accuracy.

Keywords: extrinsic calibration; calibration using; calibration; offline gnss; camera extrinsic; gnss camera

Journal Title: IEEE Robotics and Automation Letters
Year Published: 2023

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