{"id":13438837,"url":"https://github.com/HuangCongQing/plane_fit_ground_filter","last_synced_at":"2025-03-20T06:31:32.885Z","repository":{"id":107569537,"uuid":"333684828","full_name":"HuangCongQing/plane_fit_ground_filter","owner":"HuangCongQing","description":"点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle 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plane_fit_ground_filter\n\n点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications\n\n@[双愚](https://github.com/HuangCongQing/) , 若fork或star请注明来源\n\n```\n@inproceedings{Zermas2017Fast,\n  title={Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications},\n  author={Zermas, Dimitris and Izzat, Izzat and Papanikolopoulos, Nikolaos},\n  booktitle={IEEE International Conference on Robotics and Automation},\n  year={2017},\n}\n```\n\n**相关算法（带中文详细注解）：https://github.com/HuangCongQing/linefit_ground_segmentation_details**\n\n## Introduction\n\n**笔记已传送到个人知识星球：https://t.zsxq.com/0fqSUPOmD**\n\nPlus: 本人创建知识星球 **【自动驾驶感知(PCL/ROS+DL)】** 专注于自动驾驶感知领域，包括传统方法(PCL点云库,ROS)和深度学习（目标检测+语义分割）方法。同时涉及Apollo，Autoware(基于ros2)，BEV感知，三维重建，SLAM(视觉+激光雷达) ，模型压缩（蒸馏+剪枝+量化等），自动驾驶模拟仿真，自动驾驶数据集标注\u0026数据闭环等自动驾驶全栈技术，欢迎扫码二维码加入，一起登顶自动驾驶的高峰！\n\n更多自动驾驶相关交流群，欢迎扫码加入：[自动驾驶感知(PCL/ROS+DL)：技术交流群汇总(新版)](https://mp.weixin.qq.com/s?__biz=MzI4OTY1MjA3Mg==\u0026mid=2247486575\u0026idx=1\u0026sn=3145b7a5e9dda45595e1b51aa7e45171\u0026chksm=ec2aa068db5d297efec6ba982d6a73d2170ef09a01130b7f44819b01de46b30f13644347dbf2#rd)\n\n\u003cimg src=\"https://github.com/HuangCongQing/HuangCongQing/assets/20675770/304e0c4d-89d2-4cee-a2a9-3c690611c9d9\" width=\"500px\"\u003e\n\n## Dataset bag\n\n数据集已处理好，放在百度网盘上，需要自己下载\n\n* kitti_2011_09_26_drive_0005_synced.bag\n* 链接: https://pan.baidu.com/s/1sYWHzF11RpyEW25cQ_iNGA  密码: b6pd\n\n## 编译\n\n将本仓库下的2个文件夹`plane_fit_ground_filter\u0026Run_based_segmentation`移动到catkin_wp/src下，然后执行下面操作\n\n```shell\n// 创建环境变量 src中运行\nmkdir -p catkin_wp/src\ncd catkin_wp/src\ncatkin_init_workspace\n\n// 编译（需要回到工作空间catkin_wp）\ncd ..\ncatkin_make  // 产生build和devel文件夹\n\n\n//设置环境变量，找到src里的功能包(每个新的shell窗口都要执行以下source devel/setup.bash)\nsource devel/setup.bash  // 不同shell，不同哦.sh  .zsh           通过设置gedit ~/.zshrc，不用每次都source\n```\n\n详情可参考：https://www.yuque.com/docs/share/e59d5c91-b46d-426a-9957-cd262f5fc241?# 《09.创建工作空间与功能包※※※》\n\n## plane_fit_ground_filter\n\n\u003e 参考：https://github.com/AbangLZU/plane_fit_ground_filter\n\n### 修改配置文件\n\n\n举例：修改输入topic,需要修改两处\n\n```bash\ncd plane_fit_ground_filter/src/plane_ground_filter_core.cpp\n# 16行  需要修改 \"/kitti/velo/pointcloud\"\nsub_point_cloud_ = nh.subscribe(\"/kitti/velo/pointcloud\", 10, \u0026PlaneGroundFilter::point_cb, this)\n\ncd plane_fit_ground_filter/plane_ground_filter.launch\n\n#第2行 修改 value=\"/kitti/velo/pointcloud\"  修改你的雷达点云话题\n\u003carg name=\"input_topic\" default=\"/kitti/velo/pointcloud\" /\u003e     \u003c!-- 输入topic   原始 default=\"/velodyne_points\"    OR /kitti/velo/pointcloud--\u003e   \n\n```\n\n\n### Run(Terminal)\n\n```\n# Terminal1\nroscore\n\n# Terminal2  注意修改bag路径\nrosbag play ~/data/KittiRawdata/2011_09_26_drive_0005_sync/kitti_2011_09_26_drive_0005_synced.bag --loop\n\n# Terminal3\nroslaunch plane_ground_filter plane_ground_filter.launch\n```\n\n### Result\n\n![result](https://cdn.nlark.com/yuque/0/2021/png/232596/1611824743464-99d29a4e-e336-492d-8ebf-ae99ec28a89e.png)\n\n## Run_based_segmentation\n\n\u003e 参考：https://github.com/VincentCheungM/Run_based_segmentation\n\n### Requirement\n\n* [PCL](https://github.com/PointCloudLibrary/pcl)\n* [ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu)\n* [ROS Velodyne_driver](https://github.com/ros-drivers/velodyne)\n\n安装`velodyne_pointcloud`  官网链接：[http://wiki.ros.org/velodyne/Tutorials/Getting%20Started%20with%20the%20Velodyne%20VLP16](https://links.jianshu.com/go?to=http%3A%2F%2Fwiki.ros.org%2Fvelodyne%2FTutorials%2FGetting%2520Started%2520with%2520the%2520Velodyne%2520VLP16)\n\n```shell\n# melodic\nsudo apt-get install ros-melodic-velodyne\n# kinetic\nsudo apt-get install ros-kinetic-velodyne\n```\n\n**修改输入Topic**\n\n\u003e Run_based_segmentation/nodes/ground_filter/groundplanfit.cpp\n\n```\n    node_handle_.param\u003cstd::string\u003e(\"point_topic\", point_topic_, \" /kitti/velo/pointcloud\");  // 输入topoc   /velodyne_points   OR  /kitti/velo/pointcloud\n\n```\n\n### 修改配置文件\n\n举例：修改输入topic\n\n```bash\ncd Run_based_segmentation/nodes/ground_filter/groundplanfit.cpp\n\n#第129行 修改  node_handle_.param\u003cstd::string\u003e(\"point_topic\", point_topic_, \"/kitti/velo/pointcloud\");  \nnode_handle_.param\u003cstd::string\u003e(\"point_topic\", point_topic_, \"/kitti/velo/pointcloud\");  // 输入topoc   /velodyne_points   OR  /kitti/velo/pointcloud\n\n```\n\n### Run(Terminal)\n\n```\ncatkin_make # 编译\n\n# Terminal1  注意修改bag路径\nrosrun points_preprocessor_usi groundplanfit\n\n# Terminal2\nrosrun points_preprocessor_usi scanlinerun\n```\n\nAnd cluster point cloud will be published as `cluster` with different label.\n\n### Result\n\n![图片](https://cdn.nlark.com/yuque/0/2021/png/232596/1611823927608-e23ab8dd-cc9e-470a-8ef6-efad1fd086a6.png)\n\n## License\n\nCopyright (c) [双愚](https://github.com/HuangCongQing/). All rights reserved.\n\nLicensed under the [BSD 3-Clause License](./LICENSE) License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHuangCongQing%2Fplane_fit_ground_filter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FHuangCongQing%2Fplane_fit_ground_filter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHuangCongQing%2Fplane_fit_ground_filter/lists"}