move_base

    1》准备导航所需要的包。

           a.ros-indigo-gampping :我们不需要修改包内的东西，所以直接安装可执行文件就好了。

 sudo apt-get install ros-indigo-slam-gmapping

           b.安装雷达的驱动（我的是robopack），直接将提供的ros驱动包拷贝到工作空间中，

           c.安装导航定位包，navigation 进入git：https://github.com/ros-planning/navigation/tree/indigo-devel，下载和自己ros版本匹配的包，解压到自己的工作空间中，

cd ~/catkin_ws
catkin_make

indigo的navigation包会出现一个依赖问题，：Orocos-bfl not found while installing navigation stack ROS indigo + Ubuntu 14.04

解决方法：
rosdep install --from-paths src --ignore-src --rosdistro indigo -y

       d.由于导航包在/cmd_val下发布的移动数据加速度会过于不友好，所以我们需要对速度做平滑处理，其实就是控制加速，一般通过滤波即可实现，在此我们采用turtlebot的平滑包即可，

　安装平滑包yocs_velocity_smoother,具体的平滑算法和输入切换请自己阅读源码。

apt-get install ros-indigo-yocs-velocity-smoother

所有的包准包好后，我们去准备启动所需的launch文件，首先是机器人地盘的启动文件base_controller.launch：

<launch>

    <param name="use_sim_time" value="false" /> <node name="link_laser" pkg="tf" type="static_transform_publisher" args="0.15 0 0.15 0 0 0 base_link laser 50"/> <node name="link_footprint" pkg="tf" type="static_transform_publisher" args="0 0 0 0 0 0 base_link base_footprint 50"/> <node pkg="odom_tf_package" type="tf_broadcaster_node" name="serial_send_recevice" output="screen"/> <include file="$(find odom_tf_package)/launch/include/rplidar_ros.launch.xml">
 </include> <arg name="node_name" value="velocity_smoother"/> <arg name="nodelet_manager_name" value="nodelet_manager"/> <arg name="config_file" value="$(find odom_tf_package)/config/yocs_velocity_smoother.yaml"/> <arg name="raw_cmd_vel_topic" value="cmd_vel"/> <arg name="smooth_cmd_vel_topic" value="smoother_cmd_vel"/> <arg name="robot_cmd_vel_topic" value="robot_cmd_vel"/> <arg name="odom_topic" value="odom"/> <!-- nodelet manager --> <node pkg="nodelet" type="nodelet" name="$(arg nodelet_manager_name)" args="manager"/> <!-- velocity smoother --> <include file="$(find yocs_velocity_smoother)/launch/velocity_smoother.launch"> <arg name="node_name" value="$(arg node_name)"/> <arg name="nodelet_manager_name" value="$(arg nodelet_manager_name)"/> <arg name="config_file" value="$(arg config_file)"/> <arg name="raw_cmd_vel_topic" value="$(arg raw_cmd_vel_topic)"/> <arg name="smooth_cmd_vel_topic" value="$(arg smooth_cmd_vel_topic)"/> <arg name="robot_cmd_vel_topic" value="$(arg robot_cmd_vel_topic)"/> <arg name="odom_topic" value="$(arg odom_topic)"/> </include> </launch>

2.然后去准备建图包的启动文件gmapping.launch

<launch>

  <arg name="scan_topic" default="scan" /> <node pkg="gmapping" type="slam_gmapping" name="slam_gmapping" output="screen" clear_params="true"> <!--because my used rtabmap_ros --> <param name="odom_frame" value="/odom""/> <!--param name="odom_frame" value="/base_controller/odom""/--> <param name="map_update_interval" value="30.0"/> <!-- Set maxUrange < actual maximum range of the Laser --> <param name="maxRange" value="5.0"/> <param name="maxUrange" value="4.5"/> <param name="sigma" value="0.05"/> <param name="kernelSize" value="1"/> <param name="lstep" value="0.05"/> <param name="astep" value="0.05"/> <param name="iterations" value="5"/> <param name="lsigma" value="0.075"/> <param name="ogain" value="3.0"/> <param name="lskip" value="0"/> <param name="srr" value="0.01"/> <param name="srt" value="0.02"/> <param name="str" value="0.01"/> <param name="stt" value="0.02"/> <param name="linearUpdate" value="0.5"/> <param name="angularUpdate" value="0.436"/> <param name="temporalUpdate" value="-1.0"/> <param name="resampleThreshold" value="0.5"/> <param name="particles" value="80"/> <!-- <param name="xmin" value="-50.0"/> <param name="ymin" value="-50.0"/> <param name="xmax" value="50.0"/> <param name="ymax" value="50.0"/> make the starting size small for the benefit of the Android client's memory... --> <param name="xmin" value="-1.0"/> <param name="ymin" value="-1.0"/> <param name="xmax" value="1.0"/> <param name="ymax" value="1.0"/> <param name="delta" value="0.05"/> <param name="llsamplerange" value="0.01"/> <param name="llsamplestep" value="0.01"/> <param name="lasamplerange" value="0.005"/> <param name="lasamplestep" value="0.005"/> <remap from="scan" to="$(arg scan_topic)"/> </node> </launch>

3，导航包（move_base）和定位(amcl)的启动文件:savvy_amcl.launch

<launch>

  <param name="use_sim_time" value="false" /> <!-- Set the name of the map yaml file: can be overridden on the command line. --> <arg name="map" default="map.yaml" /> <!--node name="map_odom" pkg="tf" type="static_transform_publisher" args="0 0 0 0 0 0 map odom 50"/--> <!-- Run the map server with the desired map --> <node name="map_server" pkg="map_server" type="map_server" args="$(find savvy)/maps/$(arg map)"/> <!-- The move_base node --> <include file="$(find savvy)/launch/move_base_amcl.launch" /> <!--zxw add Fire up AMCL--> <include file="$(find savvy)/launch/tb_amcl.launch" /> </launch>

move_base_amcl.launch:

<launch>

  <node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen" clear_params="true"> <rosparam file="$(find savvy)/config/savvyconfig/costmap_common_params.yaml" command="load" ns="global_costmap" /> <rosparam file="$(find savvy)/config/savvyconfig/costmap_common_params.yaml" command="load" ns="local_costmap" /> <rosparam file="$(find savvy)/config/savvyconfig/local_costmap_params.yaml" command="load" /> <rosparam file="$(find savvy)/config/savvyconfig/global_costmap_params.yaml" command="load" /> <rosparam file="$(find savvy)/config/savvyconfig/base_local_planner_params.yaml" command="load" /> <rosparam file="$(find savvy)/config/nav_obstacles_params.yaml" command="load" /> </node> </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>

4.导航的配置参数如下：

base_local_planner_params.yaml

controller_frequency: 2.0
recovery_behavior_enabled: false
clearing_rotation_allowed: false TrajectoryPlannerROS: max_vel_x: 0.3 min_vel_x: 0.05 max_vel_y: 0.0 # zero for a differential drive robot min_vel_y: 0.0 min_in_place_vel_theta: 0.5 escape_vel: -0.1 acc_lim_x: 2.5 acc_lim_y: 0.0 # zero for a differential drive robot acc_lim_theta: 3.2 holonomic_robot: false yaw_goal_tolerance: 0.1 # about 6 degrees xy_goal_tolerance: 0.15 # 10 cm latch_xy_goal_tolerance: false pdist_scale: 0.8 gdist_scale: 0.6 meter_scoring: true heading_lookahead: 0.325 heading_scoring: false heading_scoring_timestep: 0.8 occdist_scale: 0.1 oscillation_reset_dist: 0.05 publish_cost_grid_pc: false prune_plan: true sim_time: 2.5 sim_granularity: 0.025 angular_sim_granularity: 0.025 vx_samples: 8 vy_samples: 0 # zero for a differential drive robot vtheta_samples: 20 dwa: true simple_attractor: false

costmap_common_params.yaml

obstacle_range: 2.5
raytrace_range: 3.0
robot_radius: 0.30 inflation_radius: 0.15 max_obstacle_height: 0.6 min_obstacle_height: 0.0 observation_sources: scan scan: {data_type: LaserScan, topic: /scan, marking: true, clearing: true, expected_update_rate: 0}

global_costmap_params.yaml

global_costmap:
   global_frame: /map
   robot_base_frame: /base_link
   update_frequency: 1.0
   publish_frequency: 0 static_map: true rolling_window: false resolution: 0.01 transform_tolerance: 0.5 map_type: costmap

local_costmap_params.yaml

local_costmap:
   global_frame: /odom
   robot_base_frame: /base_link
   update_frequency: 1.0
   publish_frequency: 1.0 static_map: false rolling_window: true width: 6.0 height: 6.0 resolution: 0.01 transform_tolerance: 0.5 map_type: costmap

四，准备好以上所有的启动文件和配置参数后，我们开始创建地图和导航，

1.创建地图：

roslaunch savvy base_controller.launch   //启动地盘控制器
roslaunch savvy gmapping.launch        
roscd savvy/maps/
rosrun map_server map_saver -f mymap


然后会产生以下地图文件
mymap.pgm  mymap.yaml

2.开始导航

roslaunch savvy base_controller.launch //启动地盘控制器
roslaunch savvy savvy_amcl.launch map:=mymap.yaml
rosrun rviz rviz -d `rospack find savvy`/nav_test.rviz  

然后指定导航目标，开始自己慢慢玩吧，不过因为我的TF变换主要是里程计更新的，车体打滑或者地盘电机震荡都会积累误差，所以我们必须添加视觉里成计或者闭环检测。