Comments (13)
Actually, I have no idea why you had this problem. Did you assign correct initial pose? If not, als_ros might output nan values since likelihood calculation cannot be performed correctly.
from als_ros.
Hi, I am running the default mcl.launch
with all parameters unchanged, then I'll try again and see if it could be coming from my tf tree. Thanks
from als_ros.
So i've investigated further and still cannot see where the issue is, I have noticed that the first few cycles go like this:
it seems to initialize correctly:
MCL: x = 0 [m], y = 0 [m], yaw = 0 [deg]
Odom: x = 2.03231 [m], y = -0.199368 [m], yaw = 155.409 [deg]
total likelihood = 1.39066e-309
average likelihood = 1.39067e-309
max likelihood = 1.28457e-322
effective sample size = 0
then very quickly goes like this:
MCL: x = -1.216e-05 [m], y = -6.151e-05 [m], yaw = -0.112011 [deg]
Odom: x = 2.03231 [m], y = -0.199368 [m], yaw = 155.409 [deg]
total likelihood = 1.39066e-309
average likelihood = 1.39067e-309
max likelihood = 1.28457e-322
effective sample size = 0
then some parameters go NaN
MCL: x = -1.216e-05 [m], y = -6.151e-05 [m], yaw = -0.112011 [deg]
Odom: x = 2.03231 [m], y = -0.199368 [m], yaw = 155.409 [deg]
total likelihood = nan
average likelihood = nan
max likelihood = nan
effective sample size = nan
then at the next cycle everything is NaN
MCL: x = nan [m], y = nan [m], yaw = nan [deg]
Odom: x = 2.03231 [m], y = -0.199368 [m], yaw = 155.409 [deg]
total likelihood = nan
average likelihood = nan
max likelihood = nan
effective sample size = nan
this over the first few cycles, it pretty much goes instantly to all NaN. Do als_ros handle nan values in the laser scan?
from als_ros.
I also noted that the the measurement_model_type
0 and 1 do work correctly so it seems to indicate that the setup is correct? I tried on a Jetson Nano with Melodic and also got the exact same error.
from als_ros.
I am wondering what types of a 2D scanner do you use. How many range data is included in your scan data? If your range data is quite large more than I expected, such as 2000, als_ros might output NaN results.
from als_ros.
It's a cheap lidar, outputs 4500 points/s at 10hz so that's 450 points per scan. is that too many? should I try reducing it?
from als_ros.
Tried again with scan_step
higher, 10, 15, still the same, all NaN. Should I try reducing the size of the scan message itself? I've recorded a bag of my scan, odom and tf if ever you have time to have a look. Not sure what to try else?
from als_ros.
I'm sorry for my late reply. I found that the value of effective sample size is 0. This means that likelihood calculation for the particles does not work. I'm not sure this readon but I think your sensor might have inccorect data format for als_ros. I usually use Hokuyo 2D LiDAR. Could you please compare the format of your LiDAR and Hokuyo 2D LiDAR?
from als_ros.
hi, thanks a lot, no worries it's not urgent.
Ok interesting, do you have a bag of the hokuyo to compare? The messages are published as standard ROS LaserScan messages so i'm not sure how they could not conform to the expected format, can you precise what you mean by "incorrect data format"?
from als_ros.
Can you please show me the laser scan paramters?
float32 angle_min
float32 angle_max
float32 angle_increment
float32 time_increment
float32 scan_time
float32 range_min
float32 range_max
Also, could you please check whether your range data contains NaN values?
from als_ros.
Here it is:
angle_min: 0.0
angle_max: 6.2831854820251465
angle_increment: 0.01387016661465168
time_increment: 0.00022083002841100097
scan_time: 0.10003600269556046
range_min: 0.019999999552965164
range_max: 12.0
from als_ros.
ranges and intensities do contain NaN values, but i also tried through a laser filter to remove them and also saw the same problem:
ranges: [nan, 9.508999824523926, 13.154000282287598, 8.74899959564209, 12.890999794006348, 12.843999862670898, 12.906000137329102, 12.984000205993652, 13.07699966430664, 13.154000282287598, 13.201000213623047, 9.182999610900879, nan, 7.741000175476074, 7.60099983215332, 7.229000091552734, 7.276000022888184, 7.353000164031982, 7.414999961853027, nan, 7.4770002365112305, 7.585999965667725, 7.631999969482422, 6.4070000648498535, 6.375999927520752, 6.841000080108643, 6.763999938964844, nan, 7.183000087738037, 7.290999889373779, 7.383999824523926, 6.9029998779296875, 6.809999942779541, 6.702000141143799, 6.639999866485596, 6.531000137329102, 6.438000202178955, 6.34499979019165, 6.2829999923706055, 6.173999786376953, 6.14300012588501, 6.127999782562256, 6.204999923706055, 6.34499979019165, 6.421999931335449, 6.065999984741211, 4.390999794006348, 4.313000202178955, 4.296999931335449, 4.328999996185303, 4.265999794006348, 4.296999931335449, 4.296999931335449, 4.296999931335449, 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5.63100004196167, 5.538000106811523, 5.492000102996826, 5.538000106811523, 5.568999767303467, 5.63100004196167, 5.692999839782715, nan, nan, nan, nan, nan, nan, 3.8320000171661377, 3.7079999446868896, 3.7079999446868896, nan, 3.568000078201294, 3.50600004196167, 3.4600000381469727, 3.4130001068115234, 3.381999969482422, 3.3510000705718994, 3.305000066757202, 3.305000066757202, nan, 3.196000099182129, 3.1649999618530273, 3.180999994277954, 3.072000026702881, 3.056999921798706, 3.072000026702881, 3.2269999980926514, 3.2269999980926514, 3.2119998931884766, 3.2119998931884766, 3.134000062942505, 3.1029999256134033, 3.0880000591278076, 3.0880000591278076, 3.134000062942505, 3.9560000896453857, 3.9100000858306885, 3.9100000858306885, 3.134000062942505, 3.134000062942505, 3.8320000171661377, 3.8010001182556152, 3.7860000133514404, 3.755000114440918, 3.7239999771118164, 3.7239999771118164, 3.693000078201294, 3.677000045776367, 3.677000045776367, 3.6459999084472656, 3.6459999084472656, 1.3969999551773071, 1.3969999551773071, 1.3969999551773071, 1.38100004196167, 1.38100004196167, 1.3660000562667847, 1.38100004196167, 1.38100004196167, 1.3660000562667847, 1.38100004196167, 1.3660000562667847, 1.38100004196167, 1.3969999551773071, 2.0329999923706055, 2.0329999923706055, 2.0169999599456787, 2.0169999599456787, 2.0169999599456787, 2.0329999923706055, 2.125999927520752, nan, 2.0480000972747803, 2.0329999923706055, 2.0329999923706055, 2.0329999923706055, 1.4119999408721924, 1.38100004196167, 1.38100004196167, 1.3969999551773071, 1.5989999771118164, 1.5989999771118164, 1.9550000429153442, 1.9550000429153442, nan, 1.9550000429153442, 1.6610000133514404, 1.5520000457763672, 1.4589999914169312, 1.3660000562667847, 1.3350000381469727, 1.319000005722046, 1.3350000381469727, 1.350000023841858, 1.350000023841858, 1.350000023841858, 1.350000023841858, 1.3660000562667847, 1.38100004196167, nan, 1.38100004196167, 1.3969999551773071, 1.4119999408721924, 1.4119999408721924, 1.38100004196167, 1.3969999551773071, 1.4429999589920044, 1.4589999914169312, 1.4739999771118164, 1.4739999771118164, 1.4900000095367432, 1.50600004196167, 1.5210000276565552, 1.5369999408721924, 1.5369999408721924, 1.5679999589920044, 2.171999931335449, 2.002000093460083, 1.9859999418258667, 1.9859999418258667, 2.002000093460083, 2.0169999599456787, 2.9639999866485596, 3.009999990463257, 3.056999921798706, 3.0880000591278076, 3.1500000953674316, 3.180999994277954, nan, 2.312000036239624, 2.885999917984009, 2.8550000190734863, 2.8239998817443848, 1.319000005722046, 1.319000005722046, 1.3350000381469727, 1.350000023841858, 1.2879999876022339, 1.2419999837875366, 1.2259999513626099, 1.4589999914169312, 1.4589999914169312, 2.6070001125335693, 2.5910000801086426, 2.559999942779541, 2.5450000762939453, 2.5139999389648438, 2.497999906539917, 2.4830000400543213, 2.4670000076293945, nan, 2.063999891281128, 2.063999891281128, 2.0329999923706055, 2.002000093460083, 1.9859999418258667, 1.9709999561309814, nan, 0.37700000405311584, 0.37700000405311584, 2.2809998989105225, 2.2660000324249268, 2.2190001010894775, 2.187999963760376, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 12.79800033569336, 12.812999725341797, 12.890999794006348, 12.937000274658203, 13.015000343322754, 13.092000007629395, 13.154000282287598, nan, nan, nan, nan, 0.2150000035762787, 0.20999999344348907, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.1080000028014183, 0.1080000028014183, 0.1080000028014183, nan, 5.75600004196167, 5.709000110626221, 5.63100004196167, 5.538000106811523, 5.460999965667725, 5.39900016784668, 5.321000099182129, 5.258999824523926, 5.197000026702881, 5.135000228881836, 5.058000087738037, 5.011000156402588, 4.994999885559082, 5.058000087738037, 5.151000022888184, 5.24399995803833, 5.382999897003174, 5.460999965667725, 5.585000038146973, 5.709000110626221, 5.817999839782715, 5.910999774932861, nan, nan, nan, nan, nan, nan, nan, nan, 12.177000045776367, nan, nan, nan, 11.944000244140625, nan, 12.611000061035156, 11.89799976348877, 11.913000106811523, 11.913000106811523, 12.378999710083008, 12.331999778747559, 12.317000389099121, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 13.432999610900879, 13.38700008392334, 13.38700008392334, 13.402000427246094, 13.402000427246094, 13.418000221252441, nan, nan, 9.477999687194824]
intensities: [nan, 206.0, 54.0, 84.0, 135.0, 197.0, 210.0, 168.0, 203.0, 210.0, 151.0, 61.0, nan, 203.0, 210.0, 212.0, 216.0, 218.0, 219.0, nan, 218.0, 216.0, 77.0, 116.0, 129.0, 93.0, 58.0, nan, 54.0, 210.0, 211.0, 87.0, 216.0, 217.0, 215.0, 219.0, 220.0, 216.0, 219.0, 211.0, 214.0, 216.0, 212.0, 214.0, 214.0, 220.0, 212.0, 217.0, 222.0, 225.0, 229.0, 227.0, 229.0, 228.0, 222.0, 217.0, 223.0, nan, 177.0, nan, nan, 197.0, 210.0, 210.0, 193.0, 206.0, 215.0, nan, 213.0, nan, 113.0, 213.0, nan, nan, 84.0, 148.0, 84.0, 103.0, 168.0, 122.0, 71.0, 93.0, 77.0, 51.0, nan, 109.0, 161.0, 155.0, 215.0, 129.0, 132.0, 161.0, 119.0, nan, nan, nan, 210.0, 84.0, 64.0, nan, nan, nan, nan, nan, nan, nan, 171.0, nan, 100.0, 193.0, 217.0, 220.0, 218.0, nan, 218.0, 214.0, 211.0, nan, nan, nan, nan, 214.0, 211.0, 222.0, 220.0, 206.0, 215.0, 214.0, 213.0, 214.0, 215.0, 216.0, 222.0, 220.0, 220.0, 221.0, 215.0, nan, nan, nan, nan, nan, nan, 219.0, 212.0, 119.0, nan, 211.0, 119.0, 217.0, 226.0, 221.0, 210.0, 211.0, 135.0, nan, 210.0, 211.0, 77.0, 215.0, 229.0, 219.0, 200.0, 220.0, 203.0, 227.0, 228.0, 224.0, 223.0, 218.0, 229.0, 226.0, 232.0, 226.0, 220.0, 235.0, 228.0, 234.0, 234.0, 234.0, 233.0, 232.0, 234.0, 235.0, 236.0, 235.0, 232.0, 231.0, 239.0, 238.0, 238.0, 235.0, 236.0, 237.0, 239.0, 235.0, 240.0, 240.0, 233.0, 213.0, 236.0, 239.0, 242.0, 242.0, 241.0, 230.0, 220.0, nan, 225.0, 224.0, 227.0, 224.0, 223.0, 233.0, 228.0, 220.0, 234.0, 223.0, 228.0, 235.0, nan, 232.0, 220.0, 225.0, 226.0, 228.0, 233.0, 234.0, 236.0, 236.0, 238.0, 237.0, 235.0, 234.0, nan, nan, 236.0, 238.0, 235.0, 238.0, 235.0, 232.0, 238.0, 236.0, 238.0, 236.0, 234.0, 235.0, 236.0, 232.0, 232.0, 227.0, 226.0, 220.0, 223.0, 225.0, 227.0, 217.0, 220.0, 219.0, 219.0, 217.0, 220.0, 219.0, nan, 225.0, 225.0, 226.0, 224.0, 226.0, 231.0, 234.0, 234.0, 228.0, 236.0, 232.0, 221.0, 225.0, 227.0, 227.0, 228.0, 231.0, 228.0, 229.0, 226.0, 219.0, nan, 226.0, 233.0, 230.0, 224.0, 229.0, 221.0, nan, 226.0, 223.0, 222.0, 233.0, 235.0, 225.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 71.0, 96.0, 200.0, 212.0, 211.0, 193.0, 48.0, nan, nan, nan, nan, 229.0, 218.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 58.0, 48.0, 54.0, nan, 210.0, 223.0, 221.0, 223.0, 223.0, 223.0, 222.0, 223.0, 223.0, 224.0, 223.0, 225.0, 224.0, 221.0, 221.0, 220.0, 219.0, 223.0, 217.0, 219.0, 217.0, 210.0, nan, nan, nan, nan, nan, nan, nan, nan, 212.0, nan, nan, nan, 93.0, nan, 193.0, 106.0, 106.0, 100.0, 135.0, 211.0, 197.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 87.0, 122.0, 211.0, 96.0, 77.0, 132.0, nan, nan, 212.0]
from als_ros.
als_ros does not work if the ranges data contains NaN.
Also, I am wondering your ranges data contains values that exceed the maximum range. I cannot say this causes the problem, but it might cause the problem.
from als_ros.
Related Issues (20)
- where is local_map_name published? HOT 4
- localization issues HOT 11
- Any Description regarding SLAMMER HOT 2
- Does it support 180 degree lidar? HOT 1
- cuda problem HOT 1
- How to get the initial pose HOT 3
- Is there any plans to port this over to ROS2? HOT 2
- Estimating pose drift HOT 5
- Issue with OpenCV on ROS Noetic on Nvidia Jetson Xavier NX (Jetpack 5.1.1) HOT 1
- positioning drift HOT 1
- Yaw drift in narrow areas HOT 2
- The position of the tf of /odom is drifted away
- How to use als_ros package correctly? HOT 1
- porting to ROS2, or ROS2 equivalent for the package HOT 4
- using als_ros when no known map and slamer mode HOT 1
- Does this library support processing data from angle sensors (IMU)?
- Help for porting to ROS2 HUMBLE
- Inflation Costmap Plugin
- use the first keyscan
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from als_ros.