Hi, I'm using the navigation stack of ROS with Rviz to autonomous navigation of my dual drive robot. I'm tring to tune costmap and planner's params but I the robot is not able to avoid obstacles and walls. For example, the global planner create a good path to follow but the local plane doesn't follow it, also tuning path_distance_bias. And I don't know why sometimes it reach the goal but other times it doesn't start to "walk" and after that the SW starts with in place rotation or recovery action. Sometimes I find Trajectory Planner more reliable than DWAPlanner but It doesn't avoid obstacles.

This is my move_base launcher:

<launch>

  <node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen">

    <rosparam file="$(find robot)/param/costmap_common_params.yaml" command="load" ns="global_costmap" />
    <rosparam file="$(find robot)/param/costmap_common_params.yaml" command="load" ns="local_costmap" />

    <rosparam file="$(find robot)/param/global_costmap_params.yaml" command="load" />
    <rosparam file="$(find robot)/param/local_costmap_params.yaml" command="load" />

    <!--I tried to comment and uncomment this for selecting Planner-->
    <param name="base_local_planner" value="dwa_local_planner/DWAPlannerROS" />
    <param name="base_global_planner" value="navfn/NavfnROS"/>

    <rosparam file="$(find robot)/param/trajectory_planner_params.yaml" command="load" />
    <rosparam file="$(find robot)/param/dwa_local_planner_params.yaml" command="load" />

    <remap from="cmd_vel" to="/cmd_vel"/>
    <remap from="odom" to="odom"/>
  </node>
</launch>

This is my costmapcommon_params:

obstacle_range: 2.5   #aggiornamento della mappa solo all'interno di 2.5 metri, quindi gli ostacoli vengono considerati solo entro 2.5 metri

raytrace_range: 3.5   #spazio libero davanti al robot

# Obstacle Cost Shaping (http://wiki.ros.org/costmap_2d/hydro/inflation)
robot_radius: 0.25  # forma che visualizzo in rviz - distance a circular robot should be clear of the obstacle (kobuki: 0.18)

inflation_radius: 1.0  #distanza massima da un ostacolo che mi minimizza un certo costo: ovvero tutti i percorsi che si trovoano a distanza di un metro da un ostacolo hanno costi uguali tra loro
cost_scaling_factor: 3.0 # maggiore è il valore, minore sara' il costo della mappa (default: 10)

subscribe_to_update: true #aggiorna la mappa
map_type: costmap #mappa dei costi

observation_source: scan #tipo di sensore che passa i dati alla mappa nel nostro caso il LaserScan
scan: {sensor_frame: camera_link, data_type: LaserScan, topic: scan, marking: true, clearing: true}

This is my global costmap param:

global_costmap:
   global_frame: map
   robot_base_frame: base_footprint
   update_frequency: 1.0
   publish_frequency: 0.5
   static_map: true
   transform_tolerance: 0.5

This is my local costmap param:

local_costmap:
   global_frame: map
   robot_base_frame: base_footprint
   update_frequency: 5.0
   publish_frequency: 2.0
   static_map: false
   rolling_window: true
   width: 4.0
   height: 4.0
   resolution: 0.05
   transform_tolerance: 0.5

This is my dwa planner params:

DWAPlannerROS:

# Robot Configuration Parameters - Kobuki
  max_vel_x: 0.45  # 0.55
  min_vel_x: 0.0

  max_vel_y: 0.0  # diff drive robot
  min_vel_y: 0.0  # diff drive robot

  max_vel_trans: 0.45 # choose slightly less than the base's capability
  min_vel_trans: 0.1  # this is the min trans velocity when there is negligible rotational velocity
  trans_stopped_vel: 0.1

  # Warning!
  #   do not set min_trans_vel to 0.0 otherwise dwa will always think translational velocities
  #   are non-negligible and small in place rotational velocities will be created.

  max_vel_theta: 1.0  # choose slightly less than the base's capability
  min_vel_theta: 0.4  # this is the min angular velocity when there is negligible translational velocity
  theta_stopped_vel: 0.4

  acc_lim_x: 1.5 # maximum is theoretically 2.0, but we
  acc_lim_theta: 2.0
  acc_lim_y: 0.0      # diff drive robot

# Goal Tolerance Parameters
  yaw_goal_tolerance: 0.15  # 0.05
  xy_goal_tolerance: 0.15  # 0.10
  # latch_xy_goal_tolerance: false

# Forward Simulation Parameters
  sim_time: 2.0       # 1.7
  vx_samples: 20       # 3
  vy_samples: 1       # diff drive robot, there is only one sample
  vtheta_samples: 20  # 20

# Trajectory Scoring Parameters
  path_distance_bias: 8.0      # 32.0   - weighting for how much it should stick to the global path plan
  goal_distance_bias: 0.8      # 24.0   - wighting for how much it should attempt to reach its goal
  occdist_scale: 0.30           # 0.01   - weighting for how much the controller should avoid obstacles
  forward_point_distance: 0.325 # 0.325  - how far along to place an additional scoring point
  stop_time_buffer: 0.2         # 0.2    - amount of time a robot must stop in before colliding for a valid traj.
  scaling_speed: 0.25           # 0.25   - absolute velocity at which to start scaling the robot's footprint
  max_scaling_factor: 0.2       # 0.2    - how much to scale the robot's footprint when at speed.

# Oscillation Prevention Parameters
  oscillation_reset_dist: 0.05  # 0.05   - how far to travel before resetting oscillation flags

# Debugging
  publish_traj_pc : true
  publish_cost_grid_pc: true
  global_frame_id: odom


# Differential-drive robot configuration - necessary?
#  holonomic_robot: false

This is my trajectory plannes params:

TrajectoryPlannerROS:
  # Robot Configuration Parameters
  acc_lim_x: 0.8
  acc_lim_theta: 1.67

  max_vel_x: 0.5
  min_vel_x: 0.2

  max_vel_theta: 1.0
  min_vel_theta: -1.0
  min_in_place_vel_theta: 0.4#0.4

  holonomic_robot: false
  escape_vel: -0.1

  # Goal Tolerance Parameters
  yaw_goal_tolerance: 0.2
  xy_goal_tolerance: 0.3
  latch_xy_goal_tolerance: false

  # Forward Simulation Parameters
  sim_time: 2.0
  sim_granularity: 0.02
  angular_sim_granularity: 0.02
  vx_samples: 10 #Antes estaba a 6, asi puede necesitar mas procesamiento pero ira mejor
  vtheta_samples: 20
  controller_frequency: 10.0

  # Trajectory scoring parameters
  meter_scoring: true # Whether the gdist_scale and pdist_scale parameters should assume that goal_distance and path_distance are expressed in units of meters or cells. Cells are assumed by default (false).
  occdist_scale:  0.1 #The weighting for how much the controller should attempt to avoid obstacles. default 0.01
  pdist_scale: 0.6  #     The weighting for how much the controller should stay close to the path it was given . default 0.6
  gdist_scale: 0.8 #     The weighting for how much the controller should attempt to reach its local goal, also controls speed  default 0.8

  heading_lookahead: 0.325  #How far to look ahead in meters when scoring different in-place-rotation trajectories
  heading_scoring: false  #Whether to score based on the robot's heading to the path or its distance from the path. default false
  heading_scoring_timestep: 0.8   #How far to look ahead in time in seconds along the simulated trajectory when using heading scoring (double, default: 0.8)
  dwa: false #Whether to use the Dynamic Window Approach (DWA)_ or whether to use Trajectory Rollout
  simple_attractor: false
  publish_cost_grid_pc: true

I tried to tune all of these params but I can't obtain a good result of navigation also reading a lot of guide for tuning. And sometimes these params are not loaded so I have to terminate "roscore" and restart it.

Can you check these params and give me some tips? Thanks