Rplidar学习（五）—— rplidar使用cartographer_ros进行地图云生成

一、Cartographer简介

　　Cartographer是google开源的通用2D和3D定位与地图同步构建的SLAM工具，并提供ROS接口。官网地址：https://github.com/googlecartographer

二、安装方法

1、安装全部依赖项

sudo apt-get update
sudo apt-get install -y \
cmake \
g++ \
git \
google-mock \
libboost-all-dev \
libeigen3-dev \
libgflags-dev \
libgoogle-glog-dev \
liblua5.-dev \
libprotobuf-dev \
libsuitesparse-dev \
libwebp-dev \
ninja-build \
protobuf-compiler \
python-sphinx \
ros-kinetic-tf2-eigen \
libatlas-base-dev \
libsuitesparse-dev \
liblapack-dev

2、安装ceres solver，下载安装在主目录下，由于googlesource.com需要FQ，这里使用hitcm（张明明）的github地址

# Build and install Ceres.
# git clone https://ceres-solver.googlesource.com/ceres-solver
# cd ceres-solver
git clone https://github.com/hitcm/ceres-solver-1.11.0.git
cd ceres-solver-1.11.
mkdir build
cd build
cmake .. -G Ninja
ninja
ninja test
sudo ninja install

3、安装cartographer，下载安装在主目录下，这里同样使用的是hitcm（张明明）的github地址

# Build and install Cartographer.
git clone https://github.com/hitcm/cartographer.git
cd cartographer
mkdir build
cd build
cmake .. -G Ninja
ninja
ninja test
sudo ninja install

4、安装cartographer_ros，这里使用的是hitcm（张明明）的github地址，由于google官方的教程需要FQ下载一些文件，因此容易失败，经验证hitcm（张明明）对原文件进行了少许修改后可以成功安装，在他的修改中核心代码不变，只修改了编译文件。

# Install wstool and rosdep.
sudo apt-get update
sudo apt-get install -y python-wstool python-rosdep ninja-build
# Create a new workspace in 'catkin_ws'.
mkdir catkin_ws
cd catkin_ws
wstool init src
# 下载到catkin_ws下面的src文件夹下面
cd src
git clone https://github.com/hitcm/cartographer_ros.git
# 然后到catkin_ws下面运行catkin_make安装 （会失败，所以根据提示改变命令）
cd
cd catkin_ws
catkin_make
source ./devel/setup.zsh

5、改变命令进行编译

catkin_make_isolated --install --use-ninja

6、修改cartographer_ros--cartographer_ros--launch--demo_revo_lds.launch

    <launch>  

      <param name="/use_sim_time" value="true" />
      <node name="cartographer_node" pkg="cartographer_ros"
          type="cartographer_node" args="
              -configuration_directory $(find cartographer_ros)/configuration_files
              -configuration_basename revo_lds.lua"
          output="screen">
        <remap from="scan" to="scan" />
      </node>
      <node name="rviz" pkg="rviz" type="rviz" required="true"
          args="-d $(find cartographer_ros)/configuration_files/demo_2d.rviz" />
    </launch>

　　修改cartographer_ros--cartographer_ros--configuration_files--revo_lds.lua

options = {

  map_builder = MAP_BUILDER,

  sensor_bridge = {

    horizontal_laser_min_range = 0.3,

    horizontal_laser_max_range = ,

    horizontal_laser_missing_echo_ray_length = 1.2,

    constant_odometry_translational_variance = .,

    constant_odometry_rotational_variance = .,

  },

  map_frame = "map",

  tracking_frame = "laser",

  published_frame = "laser",

  odom_frame = "odom",

  provide_odom_frame = true,

  use_odometry_data = false,

  use_constant_odometry_variance = true,

  constant_odometry_translational_variance = 1e-,

  constant_odometry_rotational_variance = 1e-,

  use_horizontal_laser = true,

  use_horizontal_multi_echo_laser = false,

  horizontal_laser_min_range = 0.1,

  horizontal_laser_max_range = .,

  horizontal_laser_missing_echo_ray_length = .,

  num_lasers_3d = ,

  lookup_transform_timeout_sec = 0.2,

  submap_publish_period_sec = 0.3,

  pose_publish_period_sec = 5e-,

}

MAP_BUILDER.use_trajectory_builder_2d = true

TRAJECTORY_BUILDER_2D.use_imu_data = false

TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true

SPARSE_POSE_GRAPH.optimization_problem.huber_scale = 1e2

return options

　　修改完以上2个文件重新编译一下，命令行输入

catkin_make_isolated --install --use-ninja

7、运行

　　最后命令行中运行rplidar的Node和launch文件

roslaunch rplidar_ros rplidar.launch
roslaunch cartographer_ros demo_revo_lds.launch