A Buddy Temporal-Spatial Calibration Method for Airborne Sensors in Multi-UAV Systems

The temporal and spatial relationships among various onboard sensors are crucial for ensuring the accuracy of visual observations carried out by the multiple unmanned aerial vehicles (multi-UAV) system. To leverage the integration within the multi-UAV system, we propose a buddy calibration method focused on calibrating the relative time offset and rotation parameters between the airborne camera and flight controller. We designate another UAV as the target and perform 6D pose estimation to calculate the relative pose between the camera mounted on the host UAV and the target UAV. Subsequently, we use the pose estimation results and the parameters recorded by the sensors on both UAVs to establish a comprehensive temporal and spatial calibration model. Finally, a specific method is developed to effectively solve the proposed model. Our approach was validated using two-UAV flight experiments. The results demonstrate a significant improvement, with leader attitude estimation errors decreasing to approximately less than 1
$^{\circ }$
post-calibration compared to pre-calibration. Furthermore, positioning errors for dynamic and static targets were substantially reduced over 42.59% and 53.36%, respectively.