结构光照相机和重复激光雷达的自动外部校准

IF 1.9 4区 计算机科学 Q3 ROBOTICS Robotica Pub Date : 2024-04-11 DOI:10.1017/s0263574724000444
Yangtao Ge, Chen Yao, Zirui Wang, Bangzhen Huang, Haoran Kang, Wentao Zhang, Zhenzhong Jia, Jing Wu
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引用次数: 0

摘要

将照相机和激光雷达技术相结合,可以提供互补的建筑信息,从而大大提高建筑机器人的感知能力。结构光摄像机(SLC)是一种理想的选择,因为它能提供有关建筑缺陷的全面信息。然而,这两种信息的融合在很大程度上取决于传感器的相对位置,而这只能通过外部校准来确定。本文介绍了一种新颖的校准算法,它考虑到了为 SLC 和重复激光雷达定制的校准板,旨在促进建筑机器人的自动化。校准板上装有四个对称分布的半球,其中心是通过拟合球面和采用几何约束条件得到的。随后,球心作为参考特征来估算传感器之间的关系。这些独特的特征使我们提出的方法只需要一个校准板姿势,并最大限度地减少了人为干预。我们进行了模拟和实际实验来评估我们算法的性能。结果表明,我们的方法具有更高的准确性和鲁棒性。
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Automatic extrinsic calibration for structured light camera and repetitive LiDARs
The integration of camera and LiDAR technologies has the potential to significantly enhance construction robots’ perception capabilities by providing complementary construction information. Structured light cameras (SLCs) are a desirable alternative as they provide comprehensive information on construction defects. However, fusing these two types of information depends largely on the sensors’ relative positions, which can only be established through extrinsic calibration. This paper introduces a novel calibration algorithm considering a customized board for SLCs and repetitive LiDARs, which are designed to facilitate the automation of construction robots. The calibration board is equipped with four symmetrically distributed hemispheres, whose centers are obtained by fitting the spheres and adoption with the geometric constraints. Subsequently, the spherical centers serve as reference features to estimate the relationship between the sensors. These distinctive features enable our proposed method to only require one calibration board pose and minimize human intervention. We conducted both simulation and real-world experiments to assess the performance of our algorithm. And the results demonstrate that our method exhibits enhanced accuracy and robustness.
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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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