LACI: Low-effort Automatic Calibration of Infrastructure Sensors

Johannes Müller, M. Herrmann, Jan Strohbeck, Vasileios Belagiannis, M. Buchholz
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引用次数: 7

Abstract

Sensor calibration usually is a time consuming yet important task. While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping field of view (FOV), within this work, a cooperative intelligent vehicle is used as callibration target. The vehicle is detected in the sensor frame and then matched with the information received from the cooperative awareness messages send by the coperative intelligent vehicle. The presented algorithm is fully automated as well as sensor-independent, relying only on a very common set of assumptions. Due to the direct registration on the world frame, no overlapping FOV is necessary. The algorithm is evaluated through experiment for four laserscanners as well as one pair of stereo cameras showing a repetition error within the measurement uncertainty of the sensors. A plausibility check rules out systematic errors that might not have been covered by evaluating the repetition error.
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LACI:基础设施传感器的低工作量自动校准
传感器校准通常是一项耗时而又重要的任务。传统的方法是特定于传感器的,通常需要标定目标以及广泛重叠的视场(FOV),在这项工作中,使用协作智能车辆作为标定目标。在传感器框架中检测车辆,然后与从协作智能车辆发送的协作感知消息中接收到的信息进行匹配。所提出的算法是完全自动化的,并且与传感器无关,仅依赖于一组非常常见的假设。由于在世界框架上直接注册,没有重叠的视场是必要的。通过四台激光扫描仪和一对立体摄像机的实验对该算法进行了评估,结果表明传感器的测量不确定度存在重复误差。合理性检查排除了通过评估重复错误可能无法涵盖的系统错误。
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