本文提出了一个通用多相机视觉SLAM框架,以及相关的数据集。代码开源在MultiCamSLAM。 问题描述 所提出的通用视觉SLAM pipeline如下图所示。 令使用的相机数量为Nc,每个相机cp相对于body系的外参为BTp={BRp,Btp},内参为Kp。关键帧记为xn∈SE(3),n∈1...N,对应的body位姿为wTB。路标点记为lm∈R3,m∈1...M...
To counter such problems, we propose a panoramic vision SLAM method based on multi-camera collaboration, aiming at utilizing the characters of panoramic vision and stereo perception to improve the localization precision in off-road environments. At the same time, the independence and information ...
In recent years many vision based systems that perform simultaneous localization and mapping (SLAM) have been presented and released as open source. In this paper, we extend and improve upon a state-of-the-art SLAM to make it applicable to arbitrary, rigidly coupled multi-camera systems (MCS)...
Self-Calibration and Visual SLAM with a Multi-Camera System on a Micro Aerial Vehicle 来自 学术范 喜欢 0 阅读量: 89 作者:L Heng,GH Lee,M Pollefeys 摘要: The use of a multi-camera system enables a robot to obtain a surround view, and thus, maximize its perceptual awareness of its ...
Visual SLAM is an area of vivid research and bears countless applications for moving robots. In particular, micro aerial vehicles benefit from visual sensors due to their low weight. Their motion is, however, often faster and more complex than that of ground-based robots which is why systems ...
本发明涉及一种基于Multi‑Camera/Lidar/IMU的多传感器SLAM方法,由多目相机获得的多张图像数据与IMU惯性测量单元获得的数据进行紧耦合联合初始化,获得系统的初始位姿;由激光雷达传感器获得激光雷达帧的点云数据,对点云数据进行预处理,将点云划分为强角点、弱角点、强平面点、弱平面点;通过系统的初始位姿对激光雷达帧...
学术范收录的Conference SLAM-based automatic extrinsic calibration of a multi-camera rig,目前已有全文资源,进入学术范阅读全文,查看参考文献与引证文献,参与文献内容讨论。学术范是一个在线学术交流社区,收录论文、作者、研究机构等信息,是一个与小木虫、知乎类
文档标题《Visual SLAM with a Multi-Camera Rig - College of Computing》,总页数为10页,主要介绍了与Visual SLAM with a Multi-Camera Rig - College of Computing相关的资料,希望对大家有用,欢迎大家浏览! 文档格式: .pdf 文档大小: 473.33K 文档页数: ...
SLAM-based的方法虽然不需要一个先验地图, 但是需要一个帧间匹配的穷举搜索, 还需要回环检测(有时候会失效).通过基于先验地图, 我们移除了寻找帧间匹配和回环的需求, 我们也不需要做全局BA. 我们方案更加简单, 鲁邦, 计算更加轻量."The world is a giant chessboard."...
6. Build MultiCol-SLAM: Ubuntu: This is tested with Ubuntu 16.04. Before you build MultiCol-SLAM, you have to build and install OpenCV and Pangolin. This can for example be done by running the following: Build Pangolin: sudo apt-get install libglew-dev cmake git clone https://github.com...