problem with movement goal
Hello, friends. I'm trying to realize movement goal with a rplidar. And below are my tf and nodes frame. I want the move_base node to tell me how to approach a spot in language by TTS. After I run all the nodes, It doesn't seem to work. I got warnings like this:
http://chuantu.biz/t5/112/1497967202x...
Meanwhile my PC runs slowly feels like overloading. I have ran the fake_move_base demo several times but it goes fluently. Can you help me fix this problem? Thank you so much! 
#####fake_move_base.launch##### <launch>
<node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen" clear_params="true">
<rosparam file="$(find rbx1_nav)/config/fake/costmap_common_params.yaml" command="load" ns="global_costmap" />
<rosparam file="$(find rbx1_nav)/config/fake/costmap_common_params.yaml" command="load" ns="local_costmap" />
<rosparam file="$(find rbx1_nav)/config/fake/local_costmap_params.yaml" command="load" />
<rosparam file="$(find rbx1_nav)/config/fake/global_costmap_params.yaml" command="load" />
<rosparam file="$(find rbx1_nav)/config/fake/base_local_planner_params.yaml" command="load" />
</node>
</launch>
#####costmap_common_params.yaml######
obstacle_range: 2.5
raytrace_range: 3.0
#footprint: [[0.175, 0.175], [0.175, -0.175], [-0.175, -0.175], [-0.175, 0.175]]
#footprint_inflation: 0.01
robot_radius: 0.175
inflation_radius: 0.2
max_obstacle_height: 0.6
min_obstacle_height: 0.0
observation_sources: scan
#####global_costmap_params.yaml######
global_costmap:
global_frame: map
robot_base_frame: base_footprint
update_frequency: 1.0
publish_frequency: 1.0
static_map: true
rolling_window: false
resolution: 0.01
transform_tolerance: 1.0
map_type: costmap
#####local_costmap_params.yaml######
local_costmap:
global_frame: map
robot_base_frame: base_footprint
update_frequency: 3.0
publish_frequency: 1.0
static_map: true
rolling_window: false
width: 6.0
height: 6.0
resolution: 0.01
transform_tolerance: 1.0scan: {data_type: LaserScan, topic: /scan, marking: true, clearing: true, expected_update_rate: 0}
The control loops are running extremely slowly. What PC are you running this on? Can you tell us the CPU and RAM etc.
I run this on my laptop with CPU of a i5-4210M and RAM of 4GB DDRL. And the GPU is GTX850M. I think such load isn't to heavy for my computer to run on. Is it possible that I have some configuration set improperly?
Something is chewing up your processing power. I would run the nodes 1 by 1, where possible, to see which is causing it. The rplidar node would be my first guess, as processing lidar data is intensive. Also this isn't the issue, but base_link should be the child of base_footprint and be static.
Thank you ufr3c_tjc : D I just followed what you suggested and upload the screen shot. It seems that the move_base node take the main responsibility. Everything goes well before I give the goal, and then the move_base occupies more than 100% CPU. How am I supposed to deal with it?
Makes sense. Can you edit the question to include the contents of the YAML files for
move_base? There should be about 6: 3 for costmaps, 1 each for local and global planner, and 1 for move_base itself.Yep, I've included the YAML files for move_base. Actually it's an original version of tutorial.
I don't the see the yaml files.
Can you see it now?
Please add them as text, not screenshot. You can use the "preformatted text" option to format them.
I'm sorry. And it's done.
I don't see anything wrong in them. Check with "top" what nodes are using most processing power. When overheating the CPU will reduce the clock frequency to cool down. Check with dmesg if that happens to your.
(1/2) The only thing I can see is that the costmaps are both fixed, and that the global costmap has no size set. Try setting a size for the global map. Also maybe try setting the local costmap to be a rolling window, so that it moves with the robot.
(2/2) Also try make sure that the robot stays within the bounds of the costmaps. I'm unsure what happens when it moves outside the costmaps, but it seems that yours has moved outside (judging by the local costmap size and the screenshot). However I don't think these will solve your issue.
Thank you so much for not forsaking me, my friends. I think I've found the reason. When I run those processed above with a smaller yamp map, everything seems works fine. So I guess it's the problem of size of the map.
By the way, how can I save a smaller map? I always get 4096*4096 pixels maps with map_saver which is too large to work on. I did not find where to adjust the parameter.
Tune the delta (resolution) parameter of gmapping
The size of the map is 16.8Mb. How to reduce it?