HuangCongQing / plane_fit_ground_filter

点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications

plane_fit_ground_filter

点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications

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@inproceedings{Zermas2017Fast,
  title={Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications},
  author={Zermas, Dimitris and Izzat, Izzat and Papanikolopoulos, Nikolaos},
  booktitle={IEEE International Conference on Robotics and Automation},
  year={2017},
}

相关算法（带中文详细注解）：https://github.com/HuangCongQing/linefit_ground_segmentation_details

Introduction

笔记：https://t.zsxq.com/0fqSUPOmD

Dataset bag

数据集已处理好，放在百度网盘上，需要自己下载

• kitti_2011_09_26_drive_0005_synced.bag
• 链接: https://pan.baidu.com/s/1sYWHzF11RpyEW25cQ_iNGA 密码: b6pd

编译

将本仓库下的2个文件夹plane_fit_ground_filter&Run_based_segmentation移动到catkin_wp/src下，然后执行下面操作

// 创建环境变量 src中运行
mkdir -p catkin_wp/src
cd catkin_wp/src
catkin_init_workspace

// 编译（需要回到工作空间catkin_wp）
cd ..
catkin_make  // 产生build和devel文件夹


//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)
source devel/setup.bash  // 不同shell，不同哦.sh  .zsh           通过设置gedit ~/.zshrc，不用每次都source

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※※※》

plane_fit_ground_filter

参考：https://github.com/AbangLZU/plane_fit_ground_filter

修改配置文件

举例：修改输入topic,需要修改两处

cd plane_fit_ground_filter/src/plane_ground_filter_core.cpp
# 16行  需要修改 "/kitti/velo/pointcloud"
sub_point_cloud_ = nh.subscribe("/kitti/velo/pointcloud", 10, &PlaneGroundFilter::point_cb, this)

cd plane_fit_ground_filter/plane_ground_filter.launch

#第2行 修改 value="/kitti/velo/pointcloud"  修改你的雷达点云话题
<arg name="input_topic" default="/kitti/velo/pointcloud" />     <!-- 输入topic   原始 default="/velodyne_points"    OR /kitti/velo/pointcloud-->   

Run(Terminal)

# Terminal1
roscore

# Terminal2  注意修改bag路径
rosbag play ~/data/KittiRawdata/2011_09_26_drive_0005_sync/kitti_2011_09_26_drive_0005_synced.bag --loop

# Terminal3
roslaunch plane_ground_filter plane_ground_filter.launch

Result

Run_based_segmentation

参考：https://github.com/VincentCheungM/Run_based_segmentation

Requirement

• PCL
• ROS Kinetic
• ROS Velodyne_driver

安装velodyne_pointcloud 官网链接：http://wiki.ros.org/velodyne/Tutorials/Getting%20Started%20with%20the%20Velodyne%20VLP16

# melodic
sudo apt-get install ros-melodic-velodyne
# kinetic
sudo apt-get install ros-kinetic-velodyne

修改输入Topic

Run_based_segmentation/nodes/ground_filter/groundplanfit.cpp

    node_handle_.param<std::string>("point_topic", point_topic_, " /kitti/velo/pointcloud");  // 输入topoc   /velodyne_points   OR  /kitti/velo/pointcloud

修改配置文件

举例：修改输入topic

cd Run_based_segmentation/nodes/ground_filter/groundplanfit.cpp

#第129行 修改  node_handle_.param<std::string>("point_topic", point_topic_, "/kitti/velo/pointcloud");  
node_handle_.param<std::string>("point_topic", point_topic_, "/kitti/velo/pointcloud");  // 输入topoc   /velodyne_points   OR  /kitti/velo/pointcloud

Run(Terminal)

catkin_make # 编译

# Terminal1  注意修改bag路径
rosrun points_preprocessor_usi groundplanfit

# Terminal2
rosrun points_preprocessor_usi scanlinerun

And cluster point cloud will be published as cluster with different label.

Result

License

Copyright (c) 双愚. All rights reserved.

Licensed under the BSD 3-Clause License License.