AMCL是机器人在二维移动过程中概率定位系统。它应用自适应的蒙特卡洛定位方式（或者KLD采样），采用微粒过滤器来跟踪已知地图中机器人的位姿。

如果看到LZ之前的几篇的博客,一路下来,建图后,怎么让机器人知道自己在哪儿呢?这就需要amcl了.

还是,第一步打开ros的master

roscore

连接自己的机器人

roslaunch felaim_2dnav felaim_robot.launch

连接kinect生成雷达数据

roslaunch felaim_2dnav pioneer3at_fake_laser_freenect.launch

运行amcl节点

roslaunch felaim_2dnav tb_demo_amcl.launch

tb_demo_amcl.launch

<launch> <param name="use_sim_time" value="false" /> <!-- EDIT THIS LINE TO REFLECT THE NAME OF YOUR OWN MAP FILE Can also be overridden on the command line --> <arg name="map" default="my_map.yaml" /> <!-- Run the map server with the desired map --> <node name="map_server" pkg="map_server" type="map_server" args="$(find felaim_2dnav)/maps/$(arg map)"/> <!-- Start move_base --> <include file="$(find felaim_2dnav)/launch/tb_move_base.launch" /> <!-- Fire up AMCL --> <include file="$(find felaim_2dnav)/launch/tb_amcl.launch" /> </launch>

tb_amcl.launch

<launch> <arg name="use_map_topic" default="false"/> <arg name="scan_topic" default="scan"/> <node pkg="amcl" type="amcl" name="amcl" clear_params="true"> <param name="use_map_topic" value="$(arg use_map_topic)"/> <!-- Publish scans from best pose at a max of 10 Hz --> <param name="odom_model_type" value="diff"/> <param name="odom_alpha5" value="0.1"/> <param name="gui_publish_rate" value="10.0"/> <param name="laser_max_beams" value="60"/> <param name="laser_max_range" value="12.0"/> <param name="min_particles" value="500"/> <param name="max_particles" value="2000"/> <param name="kld_err" value="0.05"/> <param name="kld_z" value="0.99"/> <param name="odom_alpha1" value="0.2"/> <param name="odom_alpha2" value="0.2"/> <!-- translation std dev, m --> <param name="odom_alpha3" value="0.2"/> <param name="odom_alpha4" value="0.2"/> <param name="laser_z_hit" value="0.5"/> <param name="laser_z_short" value="0.05"/> <param name="laser_z_max" value="0.05"/> <param name="laser_z_rand" value="0.5"/> <param name="laser_sigma_hit" value="0.2"/> <param name="laser_lambda_short" value="0.1"/> <param name="laser_model_type" value="likelihood_field"/> <!-- <param name="laser_model_type" value="beam"/> --> <param name="laser_likelihood_max_dist" value="2.0"/> <param name="update_min_d" value="0.25"/> <param name="update_min_a" value="0.2"/> <param name="odom_frame_id" value="odom"/> <param name="resample_interval" value="1"/> <!-- Increase tolerance because the computer can get quite busy --> <param name="transform_tolerance" value="1.0"/> <param name="recovery_alpha_slow" value="0.0"/> <param name="recovery_alpha_fast" value="0.0"/> <remap from="scan" to="$(arg scan_topic)"/> </node> </launch>

最后进行可视化:

rosrun rviz rviz `rospack find felaim_2dnav`/launch/nav_test.rviz

当amcl第一次启动时,需要给机器人设置一个初始方向(位置与方向),因为amcl靠自己确定的信息.为了设定初始方位,首先点击RVIZ中的2D Pose Estimation按钮.接着在地图上点击你的机器人的位置.按着鼠标箭头,会出现绿色箭头,移动箭头来使箭头的方向和机器人一致,松开鼠标.

看到你想要的图像时,点击2D New Goal按钮,接着在地图中选择一个目标位置.然后,你的机器人就愉快的奔向目的地啦O(∩_∩)O哈哈~