使用RPLIDAR A2來跑hectorslam

首先需要安裝hectorslam，方法如下：sudo apt-get install ros-indigo-hector-slam

然後安裝RPLIDAR的驅動，具體方法如下：

先插上lidar

ls -l /dev |grep ttyUSB

Add the authority of write: (such as /dev/ttyUSB0)

 sudo chmod 666 /dev/ttyUSB0

Start a rplidar node and view the scan result in rviiz

 $ roslaunch rplidar_ros view_rplidar.launch

Start a rplidar node and run rplidar client process to print the raw scan result

下面一行就可以單獨啓動rplidarA2了

 $ roslaunch rplidar_ros rplidar.launch

接下來寫幾個關鍵的launch文件  在hector_slam_launch文件夾下添加吐下介個文件：

slam.launch

<launch> <param name="/use_sim_time" value="false" /> <node pkg="rviz" type="rviz" name="rviz" args="-d $(find hector_slam_launch)/rviz_cfg/mapping_demo.rviz"/> <include file="$(find hector_slam_launch)/launch/hector_mapping.launch" /> <include file="$(find hector_slam_launch)/launch/geotiff_mapper.launch"><arg name="trajectory_source_frame_name" value="scanmatcher_frame"/> </include>  </launch>

hector_mapping.launch

<launch>
<node pkg="hector_mapping" type="hector_mapping" name="hector_mapping"   output="screen">
<param name="pub_map_odom_transform" value="true" />
<param name="map_frame" value="map" />
<param name="base_frame" value="base_link" />
<param name="odom_frame" value="base_link" />

<param name="map_resolution" value="0.050"/>
<param name="map_size" value="1048"/>
<param name="map_start_x" value="0.5"/>

<param name="map_start_y" value="0.5" />

<param name="map_multi_res_levels" value="2" />

<param name="update_factor_free" value="0.4"/>

<param name="update_factor_occupied" value="0.9" />   

<param name="map_update_distance_thresh" value="0.4"/>

<param name="map_update_angle_thresh" value="0.06" />

<param name="laser_z_min_value" value = "-1.0" />

<param name="laser_z_max_value" value = "1.0" />

</node>

 

<node pkg="tf" type="static_transform_publisher" name="base_to_laser_broadcaster" args="0 0 0 0 0 0 /base_link /laser 100" />


 

</launch>

geotiff_mapper.launch

<launch><arg  name="trajectory_source_frame_name" default="/base_link"/><arg  name="trajectory_update_rate" default="4"/><arg  name="trajectory_publish_rate" default="0.25"/> <node pkg="hector_trajectory_server" type="hector_trajectory_server" name="hector_trajectory_server" output="screen"><param name="target_frame_name" type="string" value="/map" /><param name="source_frame_name" type="string" value="$(arg trajectory_source_frame_name)" /><param name="trajectory_update_rate" type="double" value="$(arg trajectory_update_rate)" /><param name="trajectory_publish_rate" type="double" value="$(arg trajectory_publish_rate)" /></node> <node pkg="hector_geotiff" type="geotiff_node" name="hector_geotiff_node" output="screen" launch-prefix="nice -n 15"><remap from="map" to="/dynamic_map" /><param name="map_file_path" type="string" value="$(find hector_geotiff)/maps" /><param name="map_file_base_name" type="string" value="uprobotics" /><param name="geotiff_save_period" type="double" value="0" /><param name="draw_background_checkerboard" type="bool" value="true" /><param name="draw_free_space_grid" type="bool" value="true" /></node></launch>

上述建立好以後就可以使用hectorslam和rviz來查看結果了

$ roslaunch hector_slam_launch slam.launch

當掃描完以後就可以保存地圖了

Rosrun map_server map_saver –f /tmp/my_map

如果手上有turtlebot機器人的話，可以使用這個移動平臺來見圖，如何啓動移動平臺呢？方法如下：

roslaunch turtlebot_bringup minimal.launch --screen

啓動turtlebot，然後執行

roslaunch turtlebot_teleop keyboard_teleop.launch進行無線控制turtlebot

其實針對kobuki的機器人用下面的兩條語句更合適：

# This launches the minimal operation configuration> roslaunch kobuki_node minimal.launch# This launches the keyboard teloperation node# Probably you want to do this in another terminal> roslaunch kobuki_keyop keyop.launch

在安裝完ros後，建議執行一下命令安裝一些必要的ros包：

sudo apt-get install ros-indigo-turtlebot-bringup \
ros-indigo-turtlebot-create-desktop ros-indigo-openni-* \
ros-indigo-openni2-* ros-indigo-freenect-* ros-indigo-usb-cam \
ros-indigo-laser-* ros-indigo-hokuyo-node \
ros-indigo-audio-common gstreamer0.10-pocketsphinx \
ros-indigo-pocketsphinx ros-indigo-slam-gmapping \
ros-indigo-joystick-drivers python-rosinstall \
ros-indigo-orocos-kdl ros-indigo-python-orocos-kdl \
python-setuptools ros-indigo-dynamixel-motor-* \
libopencv-dev python-opencv ros-indigo-vision-opencv \
ros-indigo-depthimage-to-laserscan ros-indigo-arbotix-* \
ros-indigo-turtlebot-teleop ros-indigo-move-base \
ros-indigo-map-server ros-indigo-fake-localization \
ros-indigo-amcl git subversion mercurial