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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Simultaneous Calibration of Odometry and Head-Eye Parameters for Mobile Robots with a Pan-Tilt Camera
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Simultaneous Calibration of Odometry and Head-Eye Parameters for Mobile Robots with a Pan-Tilt Camera

机译：带有倾斜摄像机的移动机器人的里程表和头眼参数的同时校准

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摘要

In the field of robot navigation, the odometric parameters, such as wheel radii and wheelbase length, and the relative pose of the optical sensing camera with respect to the robot are very important criteria for accurate operation. Hence, these parameters are necessary to be estimated for more precise operation. However, the odometric and head-eye parameters are typically estimated separately, which is an inconvenience and requires longer calibration time. Even though several researchers have proposed simultaneous calibration methods that obtain both odometric and head-eye parameters simultaneously to reduce the calibration time, they are only applicable to a mobile robot with a fixed camera mounted, not for mobile robots equipped with a pan-tilt motorized camera systems, which is a very common configuration and widely used for wide view. Previous approaches could not provide the z-axis translation parameter between head-eye coordinate systems on mobile robots equipped with a pan-tilt camera. In this paper, we present a full simultaneous mobile robot calibration of head–eye and odometric parameters, which is appropriate for a mobile robot equipped with a camera mounted on the pan-tilt motorized device. After a set of visual features obtained from a chessboard or natural scene and the odometry measurements are synchronized and received, both odometric and head-eye parameters are iteratively adjusted until convergence prior to using a nonlinear optimization method for more accuracy.
机译：在机器人导航领域，诸如车轮半径和轴距长度之类的里程参数以及光学传感相机相对于机器人的相对姿势是精确操作的非常重要的标准。因此，这些参数对于更精确的操作来说是必需的。然而，里程和头眼参数通常是单独估计的，这是不方便的并且需要更长的校准时间。尽管一些研究人员提出了同时校准方法，该方法可以同时获取里程和头眼参数以减少校准时间，但它们仅适用于安装了固定摄像头的移动机器人，不适用于配备了云台电动的移动机器人摄影机系统，这是非常常见的配置，广泛用于宽视角。先前的方法无法在配备了云台摄像机的移动机器人上提供其头眼坐标系之间的z轴平移参数。在本文中，我们介绍了头部，眼睛和里程参数的完整同步移动机器人校准，该校准适用于在云台电动设备上配备了摄像头的移动机器人。从棋盘或自然场景获得的一组视觉特征和里程表的测量值同步并接收后，里程表参数和头眼参数都会迭代调整，直到收敛为止，然后再使用非线性优化方法以提高准确性。

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