VitorHirozawa's profile - activity

Hi, I am trying to setup a range_sensor_layer to use an ultrasonic sensor on the navigation stack. I am using move_base in a custom mobile robot. The robot uses a computer with Ubuntu 18.04.2 LTS and ROS Melodic (1.14.3). I am using one RGB-D camera and an ultrasonic sensor.

First I launch the navigation without publishing sensor_msgs/Range on its topic. Then I can navigate without the ultrasonic data. When I launch the node that publishes the Range data, the move_base node dies.

Can anybody help me to configure correctly the range_sensor_layer?

Following are my configuration files:

global_costmap_params.yaml

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

  plugins: 
    - {name: static_layer,    type: "costmap_2d::StaticLayer"}       
    - {name: inflation_layer, type: "costmap_2d::InflationLayer"}

local_costmap_param.yaml

local_costmap:
  global_frame: odom
  robot_base_frame: base_footprint
  update_frequency: 2.0
  publish_frequency: 2.0
  static_map: false
  rolling_window: true
  width: 4.0
  height: 4.0
  resolution: 0.025
  origin_x: -2.0      
  origin_y: -2.0      

  plugins:    
    - {name: obstacle_layer, type: "costmap_2d::VoxelLayer"}       
    - {name: sonar_layer,   type: "range_sensor_layer::RangeSensorLayer"}
    - {name: inflation_layer, type: "costmap_2d::InflationLayer"}

costmap_common_params.yaml

footprint: [[0.095,  -0.202], [-0.095,  -0.202], [-0.310, -0.165], [-0.310, 0.165], [-0.095, 0.202], [0.095, 0.202]]  
footprint_padding: 0.025            

#layer definitions
obstacle_layer:  
    obstacle_range: 3.5     
    raytrace_range: 4.0      

    observation_sources: point_cloud_sensor

    point_cloud_sensor: {
      sensor_frame: camera_link, 
      data_type: PointCloud2, 
      topic: openni_points, 
      expected_update_rate: 0.5, 
      marking: true, 
      clearing: true,
      min_obstacle_height: 0.0,
      max_obstacle_height: 2.0,                                                                            
      origin_z: 0.0,        
      z_resolution: 0.05,  
      z_voxels: 40,                  
      publish_voxel_map: true 
    }

sonar_layer:
      ns: /robot/sensor/
      topics: ['sonar_forward_left']                             

inflation_layer:
    inflation_radius: 1.20               
    cost_scaling_factor: 2.58                                                   

transform_tolerance: 1

controller_patience: 2.0

NavfnROS:
    allow_unknown: true

recovery_behaviors: [
    {name: conservative_clear, type: clear_costmap_recovery/ClearCostmapRecovery},
    {name: aggressive_clear, type: clear_costmap_recovery/ClearCostmapRecovery}
]

conservative_clear: 
    reset_distance: 3.00
aggressive_clear:
    reset_distance: 5.00

The navigation launch log (working good) without publishing on sensor_msgs/Range Topic:

...
[ INFO] [1560451022.672595882]: Using plugin "static_layer"
[ INFO] [1560451022.678838847]: Requesting the map...
[ INFO] [1560451022.881123086]: Resizing costmap to 279 X 208 at 0.050000 m/pix
[ INFO] [1560451022.981045216]: Received a 279 X 208 map at 0.050000 m/pix
[ INFO] [1560451022.983909307]: Using plugin "inflation_layer"
[ INFO] [1560451023.023428562]: Using plugin "obstacle_layer"
[ INFO] [1560451023.024910763]:     Subscribed to Topics: point_cloud_sensor
[ INFO] [1560451023.049016230]: Using plugin "sonar_layer"
[ INFO] [1560451023.051504866]: local_costmap/sonar_layer: ALL as input_sensor_type given
[ INFO] [1560451023.053644089]: RangeSensorLayer: subscribed to topic /robot/sensor/sonar_forward_left
[ INFO] [1560451023.065115576]: Using plugin "inflation_layer"
[ INFO] [1560451023.111015732]: Created local_planner base_local_planner/TrajectoryPlannerROS
[ INFO] [1560451023.126600417]: Sim period is set to 0.20
[ INFO] [1560451023.254282343]: Approximate time sync = true
[ERROR] [1560451023.620386435]: obstacles_detection: Parameter "min_cluster_size" has moved from rtabmap_ros to rtabmap library. Use parameter "Grid/MinClusterSize" instead. The value is still copied to new parameter name.
[ERROR] [1560451023.621727209]: obstacles_detection: Parameter "max_obstacles_height" has moved from rtabmap_ros to rtabmap library. Use parameter "Grid/MaxObstacleHeight" instead. The value is still copied to new parameter name.
[ WARN] [1560451025.131534696]: The openni_points observation buffer has not been updated for 2.10 seconds, and it should be updated every 0.50 seconds.
[ WARN] [1560451025.131593002]: The openni_points observation buffer has not been ...

Hi, I am using robot_localization package on ROS Kinetic to fuse imu data with wheel encoder odometry and generate a odometry/filtered message to navigate using AMCL for localization. My robot uses a raspberry pi 3 running Ubuntu Mate 16.04.2 and Arduino boards. It uses a Neato XV-11 Lidar for the laser scans. My launch works but the terminal does not stop to print this Warning message:

Warning: Invalid argument "/imu_frame" passed to canTransform argument source_frame in tf2 frame_ids cannot start with a '/' like: 
         at line 134 in /tmp/binarydeb/ros-kinetic-tf2-0.5.16/src/buffer_core.cpp

Also, in Rviz the topic /odometry/filtered got blinking errors at a rate of 4 Hz.

The Rviz error :

Transform [sender=unknown_publisher]
For frame [odom]: No transform to fixed frame [map]. TF error: [Lookup would require extrapolation into the future. Requested time 1516667536.039499044 but the latest data is at time 1516667536.027499399, when looking up transform from frame [odom] to frame [map]]

When it has no error:

Transform [sender=unknown_publisher]
Transform OK

What is the error in my application? Is there a solution to stop this warning?

Thank you! =)

I tried to upload images but I dont have points enough in ros answers.

My tf tree is:

Map -----/amcl (avg rate:4.05)-----> odom ----- /ekf_localization_node_odom2base (avg rate 49.5) ---> base_link

base_link ------- /tf_neato (avg rate:96.7) ------ > laser

base_link -------- /tf_imu (avg rate: 97.0) ---------> imu_frame

Here is the ekf_localization.yaml config file:

#2nd config for the 2nd node to make tf odom to base_link
#It is almost identical, just world_frame: odom. 

#Configuration for robot odometry EKF
#
frequency: 50

two_d_mode: true

publish_tf: true

base_link_frame: base_link
odom_frame: odom
map_frame: map
world_frame: odom

#meaning_matrix_config: [   X,           Y,      Z,
#                       roll,       pitch,    yaw,
#                       X/dt,        Y/dt,    Z/dt,
#                       roll/dt, pitch/dt,  yaw/dt,
#                       X/dt2,      Z/dt2,   Z/dt2]

odom0: /odom
odom0_config: [false, false, false,
               false, false, false,
               true, true, false,
               false, false, true,
               false, false, false]
odom0_differential: false

imu0: /imu
imu0_config: [false, false, false,
               false, false, true,
               false, false, false,
               false, false, true,
               true, false, false]
imu0_differential: false

Here is the terminal of my_file.launch:

... logging to /home/pi/.ros/log/a276a068-ffcc-11e7-a672-b827ebd25c92/roslaunch-pi-desktop-730.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.

started roslaunch server http://10.42.0.1:45873/

SUMMARY
========

PARAMETERS
 * /amcl/base_frame_id: base_link
 * /amcl/first_map_only: False
 * /amcl/global_frame_id: map
 * /amcl/gui_publish_rate: 10.0
 * /amcl/kld_err: 0.01
 * /amcl/kld_z: 0.99
 * /amcl/laser_lambda_short: 0.1
 * /amcl/laser_likelihood_max_dist: 2.0
 * /amcl/laser_max_beams: 100
 * /amcl/laser_max_range: -1
 * /amcl/laser_min_range: -1
 * /amcl/laser_model_type: likelihood_field
 * /amcl/laser_sigma_hit: 0.1
 * /amcl/laser_z_hit: 0.85
 * /amcl/laser_z_max: 0.0
 * /amcl/laser_z_rand: 0.15
 * /amcl/laser_z_short: 0.0
 * /amcl/max_particles: 3000
 * /amcl/min_particles: 500
 * /amcl/odom_alpha1: 0.1
 * /amcl/odom_alpha2: 0.1
 * /amcl/odom_alpha3: 0.1
 * /amcl/odom_alpha4: 0.1
 * /amcl/odom_alpha5: 0.1
 * /amcl/odom_frame_id: odom
 * /amcl/odom_model_type: diff
 * /amcl/recovery_alpha_fast: 0.0
 * /amcl/recovery_alpha_slow: 0.0
 * /amcl/resample_interval: 1
 * /amcl/save_pose_rate: 0 ...