Consistency based calibration approach for visual-laser scanner

U. Qayyum, Jonghyuk Kim
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Abstract

Recently, the robotics community has widely used color-depth (RGB-D) sensors for various applications, such as collision avoidance, navigation and robotic path planning. To effectively utilize the benefit of depth and color modalities, it is important to know the relative pose between these sensors. In this paper we proposed a theoretical and practical approach to estimate the rigid body transformation between these complimentary sensors (extrinsic calibration). The proposed work is based upon the exploitation of some common characteristics, between theses different modalities, by integrating a consistency criteria in the nonlinear optimization framework. The calibration procedure does not require any calibration object and directly operate on the visual correspondences. We have presented calibration results on low-cost built visual-laser scanner for indoor and outdoor environments. We have also compared our approach with the existing work and found the results to be more accurate.
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基于一致性的视觉激光扫描仪标定方法
近年来,机器人学界广泛使用色深(RGB-D)传感器,用于避碰、导航和机器人路径规划等各种应用。为了有效地利用深度和颜色模态的优势,了解这些传感器之间的相对姿态是很重要的。在本文中,我们提出了一种理论和实际的方法来估计这些互补传感器之间的刚体转换(外部校准)。提出的工作是基于利用这些不同模式之间的一些共同特征,通过在非线性优化框架中集成一致性准则。校准过程不需要任何校准对象,直接对可视化对应进行操作。本文介绍了室内和室外环境下低成本内置视觉激光扫描仪的校准结果。我们还将我们的方法与现有的工作进行了比较,发现结果更加准确。
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