Abstract This paper proposes a general approach to the problem of extrinsic calibration of multiple sensors of varied modalities. This is of particular relevance for intelligent vehicles, which are complex systems that often encompass several sensors of different modalities. Our approach is seamlessly integrated with the Robot Operating System (ROS) framework, and allows for the interactive positioning of sensors and labelling of data, facilitating the calibration procedure. The calibration is formulated as a simultaneous optimization for all sensors, in which the objective function accounts for the various sensor modalities. Results show that the proposed procedure produces accurate calibrations, on par with state of the art approaches which operate only for pairwise setups.

中文翻译：

---

用于智能车辆外部校准的 ROS 框架：一种多传感器、多模态方法

摘要 本文提出了一种解决不同模态的多个传感器的外在校准问题的一般方法。这对于智能车辆尤其重要，智能车辆是复杂的系统，通常包含多个不同模式的传感器。我们的方法与机器人操作系统 (ROS) 框架无缝集成，并允许传感器的交互式定位和数据标记，促进校准过程。校准被制定为对所有传感器的同时优化，其中目标函数考虑了各种传感器模式。结果表明，所提出的程序产生准确的校准，与仅对成对设置运行的最先进方法相当。