How to build a map using slam_gmapping & amcl

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While amcl is a part of ROS, I might suggest you look at HectorSLAM instead. This requires no odometry for SLAM. But, keep in mind, there is no such thing as a perfect map in this field.

You need to first save your map after mapping with gmapping. And next you can use AMCL for robot pose estimation. example for save your map : http://wiki.ros.org/slam_gmapping/Tut...

after that process, you can use amcl launch file as add your map (with your map name) in launch file.

BUT you need to laser_scan_matcher again with amcl for good odometry

<node name="map_server" pkg="map_server" type="map_server" args="$(find rover_map)/launch/amcl_map.yaml" />
<node pkg="amcl" type="amcl" name="amcl" output="screen">

   <launch>
  <arg name="use_map_topic"   default="true"/>
  <arg name="initial_pose_x"  default="0.0"/>
  <arg name="initial_pose_y"  default="0.0"/>
  <arg name="initial_pose_a"  default="0.0"/>


<param name="odom_frame_id" value="odom_combined"/>
<param name="base_frame_id" value="base_footprint"/>
<param name="global_frame_id" value="map"/>
<param name="odom_model_type" value="diff"/>

<param name="transform_tolerance" value="0.5" />
<param name="gui_publish_rate" value="10.0"/> <!-- 5 -->
<param name="laser_max_beams" value="80"/>  <!-- 30 -->
<param name="min_particles" value="100"/>
<param name="max_particles" value="4000"/>
<param name="kld_err" value="0.05"/>
<param name="kld_z" value="0.99"/>
<param name="odom_alpha1" value="0.02"/> <!-- 0.2 -->
<param name="odom_alpha2" value="0.07"/> <!-- 0.2 -->
<!-- translation std dev, m -->
<param name="odom_alpha3" value="0.08"/> <!-- 0.8 -->
<param name="odom_alpha4" value="0.02"/> <!-- 0.2 -->
<param name="laser_max_range" value="5.6"/>
<param name="laser_z_hit" value="0.95"/>
<param name="laser_z_short" value="0.1"/>
<param name="laser_z_max" value="0.05"/>
<param name="laser_z_rand" value="0.05"/>
<param name="laser_sigma_hit" value="0.2"/>
<param name="laser_lambda_short" value="0.1"/>
<param name="laser_lambda_short" value="0.1"/>
<param name="laser_model_type" value="likelihood_field"/>
<!-- <param name="laser_model_type" value="beam"/> -->
<param name="laser_likelihood_max_dist" value="2.0"/>
<param name="update_min_d" value="0.08"/>  <!-- 0.2 **0.15-->
<param name="update_min_a" value="0.18"/>  <!-- 0.5 **0.12-->

<param name="resample_interval" value="1"/>
<param name="transform_tolerance" value="0.1"/> <!-- 0.1 -->
<param name="recovery_alpha_slow" value="0.0"/>
<param name="recovery_alpha_fast" value="0.0"/>

<param name="initial_pose_x" value="$(arg initial_pose_x)"/>
<param name="initial_pose_y" value="$(arg initial_pose_y)"/>
<param name="initial_pose_a" value="$(arg initial_pose_a)"/>
<param name="use_map_topic" value="$(arg use_map_topic)"/>

</node>
</launch>

Hi!

So AMCL is going to provide a pose? Can I use hector_slam to provide AMCL with the odometry information instead of laser_scan_matcher? Therefore it would have two separated occupancyGrid topics, one with the known map, used by AMCL and one with the map created by hector_slam. The main advance of that as compared to hector_slam alone is that my path planning algorithm can leverage on the awareness of the map for more efficiency. Thanks for your help!