ethz-asl/kalibr

GitHub: ethz-asl/kalibr

Kalibr 是用于解决视觉与惯性传感器时空联合内参与外参标定的工具箱。

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![Kalibr](https://static.pigsec.cn/wp-content/uploads/repos/2026/04/b3a3c804ac222012.png) [![ROS1 Ubuntu 20.04](https://github.com/ethz-asl/kalibr/actions/workflows/docker_2004_build.yaml/badge.svg)](https://github.com/ethz-asl/kalibr/actions/workflows/docker_2004_build.yaml) [![ROS1 Ubuntu 18.04](https://github.com/ethz-asl/kalibr/actions/workflows/docker_1804_build.yaml/badge.svg)](https://github.com/ethz-asl/kalibr/actions/workflows/docker_1804_build.yaml) [![ROS1 Ubuntu 16.04](https://github.com/ethz-asl/kalibr/actions/workflows/docker_1604_build.yaml/badge.svg)](https://github.com/ethz-asl/kalibr/actions/workflows/docker_1604_build.yaml) ## 介绍 Kalibr 是一个用于解决以下校准问题的工具箱: 1. **多摄像头校准**:对具有非全局共享视野的摄像头系统进行内参和外参校准,支持广泛的 [摄像头模型](https://github.com/ethz-asl/kalibr/wiki/supported-models)。 2. **视觉-惯性校准(CAM-IMU)**:对 IMU 与摄像头系统进行空间和时间校准,同时校准 IMU 的内参。 3. **多惯性校准(IMU-IMU)**:对 IMU 与基准惯性传感器进行空间和时间校准,同时校准 IMU 的内参(需要 1 个辅助摄像头传感器)。 4. **滚动快门摄像头校准**:对滚动快门摄像头进行完整的内参校准(投影、畸变和快门参数)。 按照 [安装维基页面](https://github.com/ethz-asl/kalibr/wiki/installation) 的说明进行安装,您可以使用 Docker 或在 ROS 工作空间中从源代码安装。 请参考该 [仓库的维基页面](https://github.com/ethz-asl/kalibr/wiki) 获取更多信息。 如有问题或建议,请在 Github 上打开一个 issue。 ## 新闻 / 事件 * **2022年11月24日** - 为生成的报告新增轨迹和 IMU 速率的可视化,并修复了将姿态导出到文件的支持(参见 PR [#578](https://github.com/ethz-asl/kalibr/pull/578),[#581](https://github.com/ethz-asl/kalibr/pull/581),[#582](https://github.com/ethz-asl/kalibr/pull/582)) * **2022年5月3日** - 增加了对 Ubuntu 20.04 的支持以及 Docker 脚本,并通过 PR [#515](https://github.com/ethz-asl/kalibr/pull/515) 合并到主分支。大量工作是将 Python 升级到 3 版本。特别感谢为此做出贡献的所有贡献者。此外,还合并了对不同验证和可视化脚本的修复。 * **2020年2月3日** - 通过 PR [#241](https://github.com/ethz-asl/kalibr/pull/241) 合并了初始的 Ubuntu 18.04 支持。此外,在无法初始化焦距时,可以从命令行提供焦距的初始猜测值。 * **2018年8月15日** - 通过 PR [#210](https://github.com/ethz-asl/kalibr/pull/210) 将双球面摄像头模型贡献到该仓库。如果您感兴趣,可以参考 [论文](https://arxiv.org/abs/1807.08957) 了解仓库中模型的概述。 * **2016年8月25日** - 通过 PR [#65](https://github.com/ethz-asl/kalibr/pull/65) 添加了滚动快门摄像头校准支持。[论文](https://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Oth_Rolling_Shutter_Camera_2013_CVPR_paper.pdf) 为对此感兴趣的人提供了详细信息。 * **2016年5月18日** - 发布了对多 IMU 到 IMU 空间校准和 IMU 内参校准的支持。 * **2014年6月18日** - 仓库的初始公开发布。 ## 作者 * Paul Furgale * Hannes Sommer * Jérôme Maye * Jörn Rehder * Thomas Schneider ([email](thomas.schneider@voliro.com)) * Luc Oth ## 参考文献 Kalibr 使用的校准方法基于以下论文。在使用该工具箱或其部分进行学术发表时,请引用相应的论文。 1. Joern Rehder, Janosch Nikolic, Thomas Schneider, Timo Hinzmann, Roland Siegwart (2016). Extending kalibr: Calibrating the extrinsics of multiple IMUs and of individual axes. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4304-4311, Stockholm, Sweden. 2. Paul Furgale, Joern Rehder, Roland Siegwart (2013). Unified Temporal and Spatial Calibration for Multi-Sensor Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan. 3. Paul Furgale, T D Barfoot, G Sibley (2012). Continuous-Time Batch Estimation Using Temporal Basis Functions. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2088–2095, St. Paul, MN. 4. J. Maye, P. Furgale, R. Siegwart (2013). Self-supervised Calibration for Robotic Systems, In Proc. of the IEEE Intelligent Vehicles Symposium (IVS) 5. L. Oth, P. Furgale, L. Kneip, R. Siegwart (2013). Rolling Shutter Camera Calibration, In Proc. of the IEEE Computer Vision and Pattern Recognition (CVPR) ## 致谢 This work is supported in part by the European Union's Seventh Framework Programme (FP7/2007-2013) under grants #269916 (V-Charge), and #610603 (EUROPA2). ## 许可证 (BSD) Copyright (c) 2014, Paul Furgale, Jérôme Maye and Jörn Rehder, Autonomous Systems Lab, ETH Zurich, Switzerland
Copyright (c) 2014, Thomas Schneider, Skybotix AG, Switzerland
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标签:Bash脚本, Docker, ETH Zurich, IMU标定, ROS1, SLAM, 二进制发布, 传感器标定, 内参外参, 多传感器融合, 多相机标定, 安全防御评估, 开源工具, 惯性导航, 时空校准, 机器人感知, 滚动快门相机标定, 相机IMU联合标定, 视觉导航, 视觉惯性标定, 请求拦截, 逆向工具