Ask Your Question
0

Robot planner tuning - does not plan down the middle of small pathways

asked 2016-10-18 18:03:29 -0500

nxydes gravatar image

updated 2020-05-06 14:37:35 -0500

jayess gravatar image

Hello All,

I've had some difficulty tuning the global planner. The basic problem is the plan ends up hugging one side of the path. In this case we are using "unknown" cells to restrict the robots path. Here we want the robot to drive between low lying objects that it can not observe.

Here we can see the problem I am facing: http://imgur.com/YRjQHtm

Planning adjacent to lethal cost

It seems that the created path is not in the middle, instead it is adjacent to lethal cost cells and at times crosses over lethal cost. If the path is sufficiently wide it appears the plan stays somewhat in the middle but as the path gets smaller and smaller it eventually hugs one side.

Currently, we are using Navfn however I tested the planning behavior of global planner and it did the same or similar. I can show how that behaves too if necessary.

Move_base parameters:

edit* yikes this is unreadable, any easy way to format this?

NavfnROS: {allow_unknown: false}
TrajectoryPlannerROS: {acc_lim_th: 9.0, acc_lim_theta: 3.2, acc_lim_x: 3.0, acc_lim_y: 2.5,
  angular_sim_granularity: 0.025, dwa: false, escape_reset_dist: 0.1, escape_reset_theta: 1.57079632679,
  escape_vel: 0.0, gdist_scale: 0.8, heading_lookahead: 0.325, heading_scoring: false,
  heading_scoring_timestep: 0.1, holonomic_robot: false, max_rotational_vel: 0.5,
  max_vel_theta: 1.0, max_vel_x: 0.6, meter_scoring: true, min_in_place_rotational_vel: 0.2,
  min_in_place_vel_theta: 0.4, min_vel_theta: -1.0, min_vel_x: 0.25, occdist_scale: 0.01,
  oscillation_reset_dist: 0.05, pdist_scale: 1.2, restore_defaults: false, sim_granularity: 0.025,
  sim_time: 1.7, simple_attractor: false, vtheta_samples: 20, vx_samples: 20, xy_goal_tolerance: 0.2,
  y_vels: '-0.3,-0.1,0.1,-0.3', yaw_goal_tolerance: 0.25}
aggressive_reset: {reset_distance: 1.84}
base_global_planner: navfn/NavfnROS
base_local_planner: base_local_planner/TrajectoryPlannerROS
clearing_rotation_allowed: true
conservative_reset: {reset_distance: 3.0}
conservative_reset_dist: 3.0
controller_frequency: 10.0
controller_patience: 5.0
global_costmap:
  footprint: '[]'
  footprint_padding: 0.01
  global_frame: map
  height: 10
  inflation_layer: {cost_scaling_factor: 4.0, enabled: true, inflation_radius: 2.0}
  map_type: costmap
  obstacle_layer:
    combination_method: 1
    enabled: true
    laser_scan_sensor: {clearing: true, data_type: LaserScan, marking: true, sensor_frame: LMS151,
      topic: bottom_scan}
    laser_scan_sensor2: {clearing: true, data_type: LaserScan, marking: true, sensor_frame: TiM551,
      topic: top_scan}
    map_cloud: {clearing: true, data_type: PointCloud2, marking: true, sensor_frame: base_link,
      topic: map_pointcloud}
    max_obstacle_height: 2.0
    observation_sources: velodyne_scan map_cloud laser_scan_sensor laser_scan_sensor2
    obstacle_range: 5.0
    raytrace_range: 6.0
    track_unknown_space: true
    velodyne_scan: {clearing: true, data_type: LaserScan, marking: true, sensor_frame: velodyne,
      topic: velodyne_scan}
  obstacle_layer_footprint: {enabled: true}
  origin_x: 0.0
  origin_y: 0.0
  plugins:
  - {name: static_layer, type: 'costmap_2d::StaticLayer'}
  - {name: obstacle_layer, type: 'costmap_2d::ObstacleLayer'}
  - {name: inflation_layer, type: 'costmap_2d::InflationLayer'}
  publish_frequency: 0.0
  resolution: 0.05
  robot_base_frame: base_link
  robot_radius: 0.5
  static_layer: {enabled: true, track_unknown_space: true, unknown_cost_value: 253}
  static_map: true
  transform_tolerance: 0.3
  update_frequency: 5.0
  width: 10
local_costmap:
  footprint: '[]'
  footprint_padding: 0.01
  global_frame: map
  height: 10
  inflation_layer: {cost_scaling_factor: 0.8, enabled: true, inflation_radius: 2.0}
  map_type: costmap
  obstacle_layer:
    combination_method: 1
    enabled: true
    laser_scan_sensor: {clearing: true, data_type: LaserScan, marking: true, sensor_frame: LMS151,
      topic: bottom_scan}
    laser_scan_sensor2: {clearing: true, data_type: LaserScan, marking: true, sensor_frame: TiM551,
      topic: top_scan}
    map_cloud: {clearing: true, data_type: PointCloud2, marking: true, sensor_frame: base_link,
      topic: map_pointcloud}
    max_obstacle_height: 2.0
    observation_sources: velodyne_scan map_cloud laser_scan_sensor laser_scan_sensor2
    obstacle_range: 5.0 ...
(more)
edit retag flag offensive close merge delete

Comments

I met the same problem,the global path is not the middle of road.And sometimes navigation is failed,because the robot met the inflation_layer.Do you have solved the problem?

Yang gravatar image Yang  ( 2016-10-23 21:52:54 -0500 )edit

Yang, I have not solved the problem.

"And sometimes navigation is failed,because the robot met the inflation_layer"

This also happens a lot to me. I've been looking at the parameters on the global planner and will be looking at code but so far no luck. Let me know if you find anything

nxydes gravatar image nxydes  ( 2016-10-24 12:00:30 -0500 )edit

Hi,you can increase inflation_layer value up to 0.55 .

Yang gravatar image Yang  ( 2016-10-25 00:22:36 -0500 )edit

cosmap_commom_params.yaml is important.inflation_radius value must is bigger than robot_radius value.

Yang gravatar image Yang  ( 2016-11-15 23:11:27 -0500 )edit

2 Answers

Sort by ยป oldest newest most voted
2

answered 2017-05-17 07:05:54 -0500

mcarr gravatar image

updated 2017-05-17 07:06:30 -0500

Hi, Kaiyu Zheng provides a good disucssion on this topic in his guide "ROS Navigation Tuning Guide". Check out pages 11 & 12. Download the PDF of this guide HERE.

In short, increase your inflation_radius and decrease your cost_scaling_factor parameters in your local_costmap_params.yaml. I am using inflation_radius = 1.0 and cost_scaling_factor = 2.5. This way, the planner will prefers paths as far away from both walls as possible as this will minimise the cost.

edit flag offensive delete link more
0

answered 2020-05-06 02:00:16 -0500

942951641@qq.com gravatar image

i found that inflation_radius = 1.0 and cost_scaling_factor = 4.0, it have a better result in indoor corridor

edit flag offensive delete link more

Your Answer

Please start posting anonymously - your entry will be published after you log in or create a new account.

Add Answer

Question Tools

1 follower

Stats

Asked: 2016-10-18 17:57:52 -0500

Seen: 323 times

Last updated: May 06 '20