ROS2与3D-SLAM入门教程-li_slam_ros2算法建图

ROS2与3D-SLAM入门教程-li_slam_ros2算法建图

说明:

• 介绍如何利用li_slam_ros2算法实现3D建图
• 测试环境：ubuntu20.04 + ros2 galactic

步骤:

• 安装依赖

sudo add-apt-repository ppa:borglab/gtsam-release-4.0
sudo apt update
sudo apt install libgtsam-dev libgtsam-unstable-dev

• 下载源码

mkdir -p ~/ros2_slam_3d_ws2/src
cd ~/ros2_slam_3d_ws2/src
git clone --recursive https://github.com/rsasaki0109/li_slam_ros2

• 编译

cd ~/ros2_slam_3d_ws2
export MAKEFLAGS="-j2"
colcon build --cmake-args -DCMAKE_BUILD_TYPE=Release

测试:

• 如果使用ros1录制的包来测试，可以下载ros1bag hdl_400.bag

• 这个包需要安装ros2 bag的插件rosbag2_bag_v2进行转换，　参考方法ros2入门教程-rosbag和ros2 bag 转换

• 新终端，　打开rviz

source /opt/ros/galactic/setup.bash
cd ~/ros2_slam_3d_ws2/
rviz2 -d src/li_slam_ros2/scanmatcher/rviz/lio.rviz

• 新终端，启动li_slam_ros2

source /opt/ros/galactic/setup.bash
cd ~/ros2_slam_3d_ws2/
ros2 launch scanmatcher lio.launch.py

• 新终端，播放包

$ source /opt/ros/noetic/setup.bash
$ source /opt/ros/galactic/setup.bash
$ ros2 bag info -s rosbag_v2 dataset/hdl_400.bag

• 效果图

• 保存map.pcd和pose_graph.g2o，　保存的目录为运行lidarslam.launch.py的目录
• 目前是在~/ros2_slam_3d_ws2/目录下运行

cd ~/ros2_slam_3d_ws2/
ros2 service call /map_save std_srvs/Empty

• 打开pcd
• 如果没pcl_viewer，既需安装

sudo apt install libpcl-dev　pcl-tools

• 打开

cd ~/ros2_slam_3d_ws2/
pcl_viewer map.pcd

• 效果图

参考:

• https://github.com/rsasaki0109/li_slam_ros2