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Self calibration of multiple LIDARs and cameras on autonomous vehicles

机译:自动驾驶汽车上多个LIDAR和摄像机的自校准

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摘要

Autonomous navigation is an important field of research and, given the complexity of real world environments, most of the systems rely on a complex perception system combining multiple sensors on board, which reinforces the concern of sensor calibration. Most calibration methods rely on manual or semi-automatic interactive procedures, but reliable fully automatic methods are still missing. However, if some simple objects could be detected and identified automatically by all the sensors from several points of view, then automatic calibration would be possible on the fly. The idea proposed in this paper is to use a ball in motion in front of a set of uncalibrated sensors allowing them to detect its center along the successive positions. This set of centers generates a point cloud per sensor, which, by using segmentation and fitting techniques, allows the calculation of the rigid body transformation among all pairs of sensors. This paper proposes and describes such a method with results demonstrating its validity. (C) 2016 Elsevier B.V. All rights reserved.
机译:自主导航是一个重要的研究领域,考虑到现实环境的复杂性,大多数系统依赖于复杂的感知系统,该系统结合了船上多个传感器,这加剧了传感器校准的担忧。大多数校准方法依赖于手动或半自动交互过程,但是仍然缺少可靠的全自动方法。但是,如果所有传感器可以从多个角度自动检测并识别出一些简单的物体,则可以即时进行自动校准。本文提出的想法是在一组未校准的传感器之前使用运动中的球,从而使它们能够沿连续位置检测其中心。这组中心为每个传感器生成一个点云,通过使用分段和拟合技术,可以计算所有成对传感器之间的刚体变换。本文提出并描述了这种方法,其结果证明了其有效性。 (C)2016 Elsevier B.V.保留所有权利。

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