teonik's profile - activity

Nah, that one is for creating a steering command when the desired speed and rotation are calculated. What I need is an a

is there a standalone steering package for car-like robot? tl;dr is there a ready ROS\third-party package that takes in

I'm running costmap_2d with PointCloud2 feed from a 3D lidar as the only source. Lidar points are preliminary filtered, the ground is mostly segmented out. It is used as a singular source for the singular plugin of type ObstacleLayer.

As I'm using the output occupancy grid for use with home-made custom code, I would like to have a small portion of costmap near the robot position be published after every update as OccupancyGrid. I guess this is what local_costmap settings can be used for, right?

Well, false. The setup works the same way with and without additional YAML file for the local costmap. Even worse, I cannot get the full costmap to be published every step. The /costmap/costmap topic is being published once at the start, all the rest time only costmap/costmap_update are published. This is happening despite always_send_full_costmap: true in the config.

What and where should I write to get instant local occupancy grid published?

Below are my two YAML files and the portion in the launchfile where I run the costmapping node. I'm working in Xubuntu 16.04, ROS Kinetic.

in the launchfile:

<node name="costmap_node" pkg="costmap_2d" type="costmap_2d_node" output="screen" clear_params="true">
      <rosparam file="$(find lidar_proc)/params/costmap/costmap_common_voxel_params.yaml" command="load" ns="costmap" />
<rosparam file="$(find lidar_proc)/params/costmap/local_costmap_quan_params.yaml" command="load" ns="costmap" />
          <remap from="/cloud_in" to="/lidar/flt_out_cloud"/>
    </node>

costmap_common_voxel_params.yaml:

transform_tolerance: 0.5,
robot_base_frame: base_link,

width: 200,
height: 200,
origin_x: -150,
origin_y: -50,

resolution: 0.2,
footprint:
- [-11.2, -3.2]
- [-11.2, 3.2]
- [0.2, 3.2]
- [0.2, -3.2],
update_frequency: 10.0,
static_map: false,
publish_frequency: 10.0,
max_obstacle_height:  3.0,
min_obstacle_height:  -2, 
obstacle_range: 70.0,
raytrace_range: 70.0,
always_send_full_costmap: true,

plugins:
    - {name: obstacles,          type: "costmap_2d::VoxelLayer"}

obstacles: {
  z_resolution: 0.2,
  z_voxels: 15,
  origin_z: -2.0,
  publish_voxel_map: true,
  mark_threshold: 0.5,
  enabled: true,
  max_obstacle_height:  3.0,
  min_obstacle_height:  -2,
  obstacle_range: 70.0,
  raytrace_range: 70.0,
  inflation_radius: 0.0,
  combination_method: 1,
  observation_sources: lidar_obstacles,
  lidar_obstacles: {
       sensor_frame: /Sensor,
       data_type: PointCloud2,
       topic: /cloud_in,
       expected_update_rate: 5.0,
       observation_persistence: 0.0,
       max_obstacle_height:  3.0,
       min_obstacle_height:  -2,
       marking: true,
       clearing: false,
       raytrace_range: 70.0,
       obstacle_range: 70.0}
  }

local_costmap_quan_params.yaml:

local_costmap:
  global_frame: /map
  robot_base_frame: /base_link
  static_map: false
  rolling_window: true
  resolution: 0.2
  transform_tolerance: 0.5
  width: 20
  height: 20
  always_send_full_costmap: true,
  plugins:
    - {name: obstacles,      type: "costmap_2d::ObstacleLayer"}

I'm running costmap_2d with PointCloud2 feed from a 3D lidar as the only source. Lidar points are preliminary filtered, the ground is mostly segmented out.

It works fine with both ObstacleLayer and VoxelLayer, marking and clearing. The problem is: I want to set the marking threshold, so that a single lidar point does not immediately mark the cell as occupied. Ideally, I want the lidar observations to have some short but finite lifetime, and the cells to be marked only if they accumulate, say, 5 points at a single moment of time. And here the troubles begin.

1) as I understood, the mark_threshold parameter only works for voxel layer. Is that right? If yes, why? it makes the same perfect sense for 2d occupancy grid.

2) for the voxel layer I managed to employ the mark_threshold, but setting it to anything greater than 0.5 makes the costmap not marking anything, save for a few cells.

There is no clear and concise explanation of how this thresholding works for filling in the occupancy grid, and the documentation even contradicts itself on some occasions. Workable configs provided by people in questions puzzle me (like, mark_threshold:9 ?).

Could anyone please explain how do I achieve desired behaviour? The YAML config and launch file are below.

Xubuntu 16.04, ROS Kinetic.

in the launchfile:

<node name="costmap_node" pkg="costmap_2d" type="costmap_2d_node" output="screen" clear_params="true">
      <rosparam file="$(find lidar_proc)/params/costmap/costmap_common_voxel_params.yaml" command="load" ns="costmap" />
      <remap from="/cloud_in" to="/lidar/flt_out_cloud"/>
    </node>

costmap_common_voxel_params.yaml:

transform_tolerance: 0.5,
robot_base_frame: base_link,

width: 200,
height: 200,
origin_x: -150,
origin_y: -50,

resolution: 0.2,
footprint:
- [-11.2, -3.2]
- [-11.2, 3.2]
- [0.2, 3.2]
- [0.2, -3.2],
update_frequency: 10.0,
static_map: false,
publish_frequency: 10.0,
max_obstacle_height:  3.0,
min_obstacle_height:  -2, 
obstacle_range: 70.0,
raytrace_range: 70.0,
always_send_full_costmap: true,

plugins:
    - {name: obstacles,          type: "costmap_2d::VoxelLayer"}

obstacles: {
  z_resolution: 0.2,
  z_voxels: 15,
  origin_z: -2.0,
  publish_voxel_map: true,
  mark_threshold: 0.5,
  enabled: true,
  max_obstacle_height:  3.0,
  min_obstacle_height:  -2,
  obstacle_range: 70.0,
  raytrace_range: 70.0,
  inflation_radius: 0.0,
  combination_method: 1,
  observation_sources: lidar_obstacles,
  lidar_obstacles: {
       sensor_frame: /Sensor,
       data_type: PointCloud2,
       topic: /cloud_in,
       expected_update_rate: 5.0,
       observation_persistence: 0.0,
       max_obstacle_height:  3.0,
       min_obstacle_height:  -2,
       marking: true,
       clearing: false,
       raytrace_range: 70.0,
       obstacle_range: 70.0}
  }

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