The combination of multiple sensors is becoming necessary in robotic applications as each sensor could complement the weakness of others. Determining a precise extrinsic parameter in a fast and reliable manner between multiple sensors is essential and remains challenging. In this paper, we propose a fast, accurate, and targetless extrinsic calibration method for multiple LiDARs and cameras based on adaptive voxelization. On the theory level, we incorporate the LiDAR extrinsic calibration with the bundle adjustment method. We derive the derivatives of the cost function w.r.t. the extrinsic parameter to accelerate the optimization. On the implementation level, we apply adaptive voxelization to reduce the computation time in the process of feature correspondence matching. The robustness and accuracy of our proposed method have been verified with experiments in outdoor test scenes under multiple LiDAR-camera configurations.
翻译:由于每个传感器可以补充其他传感器的弱点,因此在机器人应用中需要结合多个传感器,因为每个传感器可以补充其他传感器的弱点。在多个传感器之间迅速和可靠地确定精确的外部参数至关重要,而且仍然具有挑战性。在本文件中,我们提议了基于适应性氧化的多种激光雷达和相机的快速、准确和无目标的外部校准方法。在理论层面,我们将激光雷达外光校准与捆绑调整方法结合起来。我们从成本函数w.r.t.的外光参数衍生物中提取出加速优化的外光学参数。在实施层面,我们应用适应性蒸化法来缩短特征通信匹配过程中的计算时间。我们拟议方法的坚固性和准确性已经通过在多个激光雷达摄像仪配置下进行的户外试验场实验得到验证。