安装导航定位包，navigation:
sudo apt-get install ros-indigo-navigation
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 :
sudo apt-get install ros-indigo-yocs-velocity-smoother
在小车的运动控制的launch中如下添加:
<!-- velocity smoother -->
<include file="$(find yocs_velocity_smoother)/launch/velocity_smoother.launch">
</include>
导航包（move_base）和定位(amcl)的启动文件:nav_amcl.launch
<launch
<param name="use_sim_time" value="false" />
<!-- Set the name of the map yaml file: can be overridden on the command line. -->
<arg name="map" default="map.yaml" />
<!--node name="map_odom" pkg="tf" type="static_transform_publisher" args="0 0 0 0 0 0 map odom 50"/-->
<!-- Run the map server with the desired map -->
<node name="map_server" pkg="map_server" type="map_server" args="$(find odom_tf_package)/maps/$(arg map)"/>
<!-- The move_base node -->
<include file="$(find odom_tf_package)/launch/move_base_amcl.launch" />
<!--add Fire up AMCL-->
<include file="$(find odom_tf_package)/launch/tb_amcl.launch" />
</launch>
move_base_amcl.launch:
<launch>
<node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen" clear_params="true">
<rosparam file="$(find odom_tf_package)/config/costmap_common_params.yaml" command="load" ns="global_costmap" />
<rosparam file="$(find odom_tf_package)/config/costmap_common_params.yaml" command="load" ns="local_costmap" />
<rosparam file="$(find odom_tf_package)/config/local_costmap_params.yaml" command="load" />
<rosparam file="$(find odom_tf_package)/config/global_costmap_params.yaml" command="load" />
<rosparam file="$(find odom_tf_package)/config/base_local_planner_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:
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 ros_car_py ros_car_py.launch //启动地盘控制器
roscd odom_tf_package/maps/
rosrun map_server map_saver -f map
然后会产生以下地图文件
map.pgm map.yaml
2.开始导航
roslaunch ros_car_py nav_amcl.launch map:=map.yaml
然后指定导航目标，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。
在rviz中点击菜单栏的2D Nav Goal,可以帮助我们设置导航的目标点