【摘要】 在高级自动驾驶中，将红外相机与激光雷达融合可实现车辆全天时、全天候精准感知周围复杂环境。精准配准是实现多传感器融合不可缺少的关键步骤，融合之前需要先实现精准配准。由于红外相机没有色彩信息，因此无法使用传统配准方法对红外相机和激光雷达进行配准，只能基于特制可加热标靶进行配准。然而，这类方法成本高昂、操作繁琐、配准距离有限且精度较低。因此，提出一种面向道路场景的红外与激光雷达配准算法，该算法无需特制标靶，可根据不同方位的车辆、行人、车道线和路杆等特征实现不同距离的精确配准。实验结果表明，该方案可以提升自动驾驶系统在夜间、雨天、大雾沙尘和逆光等恶劣环境下的鲁棒性和安全性，对于纵向距离0～100 m、横向距离-10～10 m范围内的行人、汽车等目标，该方案可以达到90%以上的配准精度。更多还原

【Abstract】 In advanced autonomous driving, the fusion of infrared camera and LiDAR can realize the vehicle’s all-day, allweather accurate perception of the surrounding complex environment. Accurate alignment is an indispensable step to realize multisensor fusion, and it is necessary to realize accurate alignment before fusion. Because infrared cameras have no color information, the traditional calibration method can be used for infrared camera and the LiDAR, and the calibration can only be performed based on a special heating target. However, such methods are costly, cumbersome to operate, and have limited calibration distances and low accuracy. Therefore, this study proposes an infrared and LiDAR calibration algorithm for road scenes. The proposed algorithm does not need a special target and can achieve accurate calibration at different distances according to the characteristics of the vehicles, pedestrians, lane lines, and road poles in different directions. Experimental results show that the proposed scheme can improve the robustness and security of automatic driving systems in harsh environments such as night, rain, fog, sand, and backlight. The proposed scheme can achieve more than 90% calibration accuracy for pedestrians and cars within longitudinal distances of 0 to 100 m and lateral distances of-10 m to 10 m.更多还原