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首页> 外文会议>Proceedings of the 17th IASTED international conference on robotics applications ; Proceedings of the 11th IASTED international conference on biomedical engineering >THREE CAMERAS FOR ROBOT POSE ESTIMATION: A TRIPLE VERSUS TWO PAIRS
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THREE CAMERAS FOR ROBOT POSE ESTIMATION: A TRIPLE VERSUS TWO PAIRS

机译：机器人姿势估计的三个摄像头：三个对

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摘要

In this paper, we propose a novel layout of cameras atop a moving robot to obtain its ego-motion. In particular, we use three cameras in perpendicular setting. This layout offers a better opportunity e.g. compared to collinear settings for studying the trade-off between the accuracy of features to track and a larger field of view. We show by real experiments and synthetic data alike that using the three cameras as a triple is more advantageous when the fields of view of the cameras are slowly changing. In this case, the triple not only provide more accurate features to track but lead also to a more accurate estimation for their 3D construction. On the contrary, for pure rotations, the fields of view are rapidly changing which offers the advantage to dealing with the three cameras as two stereo pairs with a larger field of view. The extended Kalman filter (EKF) is our real-time estimator of the robot pose.
机译：在本文中，我们提出了一种新颖的摄像机布局，以在移动的机器人上方进行自我运动。特别是，我们在垂直设置中使用了三个摄像机。这种布局提供了更好的机会，例如与共线设置进行比较，以研究要跟踪的特征的精度和更大的视野之间的权衡。我们通过真实的实验和综合数据表明，当摄像机的视场在缓慢变化时，将三个摄像机作为三元组使用将更加有利。在这种情况下，三元组不仅可以提供更精确的特征跟踪，而且还可以为其3D构造提供更准确的估算。相反，对于纯旋转，视野迅速变化，这为将三个摄像机作为两个具有较大视野的立体声对提供了优势。扩展卡尔曼滤波器（EKF）是我们对机器人姿态的实时估计。

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