Comments (3)
kjyv
commented on June 2, 2024
Did you install fcl and bindings as written in the readme?
fcl 0.5.0 and python-fcl (from https://github.com/jf---/python-fcl) (possibly disable octomap if there are errors)
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geekayman
commented on June 2, 2024
Hi, thank you for your response. I followed all the steps in the readme, but I wasn't able to import directly transform module from fcl. So I put the transform module directly into the exitation file and imported it.
from fcl import fcl, collision_data
import transform
After executing the code to find the optimal trajectory. I ended up with a segmentation error.
geekayman@geekayman-Lenovo-ideapad-330-15ICH:~/FloBaRoID$ sudo python trajectory.py --config configs/kuka_lwr4.yaml --model model/kuka_lwr4.urdf --world model/world_kuka.urdf
Error: IPOPT shared library failed to import
trajectory.py:30: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
config = yaml.load(stream)
loaded model model/kuka_lwr4.urdf
# DOFs: 7
Joints: ['lwr_0_joint', 'lwr_1_joint', 'lwr_2_joint', 'lwr_3_joint', 'lwr_4_joint', 'lwr_5_joint', 'lwr_6_joint']
# regressor outputs: 7
# links: 8 (+ 0 fake)
{0: 'lwr_base_link', 1: 'lwr_1_link', 2: 'lwr_2_link', 3: 'lwr_3_link', 4: 'lwr_4_link', 5: 'lwr_5_link', 6: 'lwr_6_link', 7: 'lwr_7_link'}
# params: 80 (94 will be identified)
loaded random structural regressor from model/kuka_lwr4.urdf.regressor.npz
loaded model model/kuka_lwr4.urdf
# DOFs: 7
Joints: ['lwr_0_joint', 'lwr_1_joint', 'lwr_2_joint', 'lwr_3_joint', 'lwr_4_joint', 'lwr_5_joint', 'lwr_6_joint']
# regressor outputs: 7
# links: 8 (+ 0 fake)
{0: 'lwr_base_link', 1: 'lwr_1_link', 2: 'lwr_2_link', 3: 'lwr_3_link', 4: 'lwr_4_link', 5: 'lwr_5_link', 6: 'lwr_6_link', 7: 'lwr_7_link'}
# params: 80 (94 will be identified)
loaded random structural regressor from model/kuka_lwr4.urdf.regressor.npz
World links: ['ground_link']
Running global optimization with NSGA2
call #1/120
wf 0.5
a [[0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3]]
b [[0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3], [0.3, 0.3, 0.3, 0.3]]
q [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
[geekayman-Lenovo-ideapad-330-15ICH:06055] *** Process received signal ***
[geekayman-Lenovo-ideapad-330-15ICH:06055] Signal: Segmentation fault (11)
[geekayman-Lenovo-ideapad-330-15ICH:06055] Signal code: Address not mapped (1)
[geekayman-Lenovo-ideapad-330-15ICH:06055] Failing at address: (nil)
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 0] /lib/x86_64-linux-gnu/libc.so.6(+0x3ef20)[0x7f91f23ecf20]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 1] /home/geekayman/.local/lib/python2.7/site-packages/fcl/fcl.so(+0x13906)[0x7f91843ac906]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 2] /home/geekayman/.local/lib/python2.7/site-packages/fcl/fcl.so(+0x33358)[0x7f91843cc358]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 3] python(+0xe2fd5)[0x55994a366fd5]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 4] python(PyEval_EvalFrameEx+0x54b0)[0x55994a37db20]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 5] python(PyEval_EvalCodeEx+0x58a)[0x55994a3762aa]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 6] python(PyEval_EvalFrameEx+0x5d2e)[0x55994a37e39e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 7] python(PyEval_EvalCodeEx+0x58a)[0x55994a3762aa]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 8] python(+0x10e1cc)[0x55994a3921cc]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [ 9] python(PyObject_Call+0x3e)[0x55994a361e6e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [10] python(PyEval_EvalFrameEx+0x2a22)[0x55994a37b092]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [11] python(PyEval_EvalCodeEx+0x58a)[0x55994a3762aa]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [12] python(+0x10df29)[0x55994a391f29]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [13] python(PyObject_Call+0x3e)[0x55994a361e6e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [14] python(PyEval_CallObjectWithKeywords+0x30)[0x55994a382140]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [15] /usr/local/lib/python2.7/dist-packages/pyOpt/pyNSGA2/nsga2.so(nsga2func+0x257)[0x7f919e1c025c]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [16] /usr/local/lib/python2.7/dist-packages/pyOpt/pyNSGA2/nsga2.so(evaluate_ind+0x5b)[0x7f919e1d2c4f]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [17] /usr/local/lib/python2.7/dist-packages/pyOpt/pyNSGA2/nsga2.so(evaluate_pop+0x73)[0x7f919e1d2bde]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [18] /usr/local/lib/python2.7/dist-packages/pyOpt/pyNSGA2/nsga2.so(nsga2+0xcc5)[0x7f919e1d4bbf]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [19] /usr/local/lib/python2.7/dist-packages/pyOpt/pyNSGA2/nsga2.so(+0x10ec8)[0x7f919e1c7ec8]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [20] python(PyEval_EvalFrameEx+0x54a)[0x55994a378bba]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [21] python(PyEval_EvalCodeEx+0x58a)[0x55994a3762aa]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [22] python(+0x10e1cc)[0x55994a3921cc]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [23] python(PyObject_Call+0x3e)[0x55994a361e6e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [24] python(PyEval_EvalFrameEx+0x2a22)[0x55994a37b092]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [25] python(PyEval_EvalCodeEx+0x58a)[0x55994a3762aa]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [26] python(+0x10e1cc)[0x55994a3921cc]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [27] python(+0x12670e)[0x55994a3aa70e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [28] python(PyObject_Call+0x3e)[0x55994a361e6e]
[geekayman-Lenovo-ideapad-330-15ICH:06055] [29] python(+0x183be3)[0x55994a407be3]
[geekayman-Lenovo-ideapad-330-15ICH:06055] *** End of error message ***
Erreur de segmentation
I tried to find the source of the error and I found that the problem came from pyOpt.
Because when I run the test "tp037.py"provided by pyopt I end up with the same error.
usr/local/lib/python2.7/site-packages/pyOpt/examples$ sudo python2 tp037.py
[sudo] Mot de passe de geekayman :
Error: IPOPT shared library failed to import
Optimization Problem -- TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Objectives:
Name Value Optimum
f 0 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 10.000000 0.00e+00 4.20e+01
x2 c 10.000000 0.00e+00 4.20e+01
x3 c 10.000000 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= 0.000000 <= 0.00e+00
g2 i -1.00e+21 <= 0.000000 <= 0.00e+00
PSQP Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0173
Total Function Evaluations: 42
Sensitivities: FD
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 24.000000 0.00e+00 4.20e+01
x2 c 12.000000 0.00e+00 4.20e+01
x3 c 12.000000 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= 0.000000 <= 0.00e+00
g2 i -1.00e+21 <= -72.000000 <= 0.00e+00
--------------------------------------------------------------------------------
SLSQP Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0006
Total Function Evaluations:
Sensitivities: FD
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 24.000000 0.00e+00 4.20e+01
x2 c 12.000000 0.00e+00 4.20e+01
x3 c 12.000000 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= 0.000000 <= 0.00e+00
g2 i -1.00e+21 <= -72.000000 <= 0.00e+00
--------------------------------------------------------------------------------
CONMIN Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0112
Total Function Evaluations: 88
Sensitivities: CS
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 23.989921 0.00e+00 4.20e+01
x2 c 12.002518 0.00e+00 4.20e+01
x3 c 12.002518 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= -0.000006 <= 0.00e+00
g2 i -1.00e+21 <= -71.999994 <= 0.00e+00
--------------------------------------------------------------------------------
COBYLA Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0141
Total Function Evaluations: 112
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 24.000000 0.00e+00 4.20e+01
x2 c 11.999999 0.00e+00 4.20e+01
x3 c 12.000000 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= 0.000000 <= 0.00e+00
g2 i -1.00e+21 <= -72.000000 <= 0.00e+00
--------------------------------------------------------------------------------
SOLVOPT Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0239
Total Function Evaluations: 201
Sensitivities: FD
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 23.999011 0.00e+00 4.20e+01
x2 c 12.000860 0.00e+00 4.20e+01
x3 c 11.999634 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= -0.000000 <= 0.00e+00
g2 i -1.00e+21 <= -72.000000 <= 0.00e+00
--------------------------------------------------------------------------------
KSOPT Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0302
Total Function Evaluations: 2210
Sensitivities: FD
Objectives:
Name Value Optimum
f -3453.76 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 23.994597 0.00e+00 4.20e+01
x2 c 11.997383 0.00e+00 4.20e+01
x3 c 11.997531 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= -0.015575 <= 0.00e+00
g2 i -1.00e+21 <= -71.984425 <= 0.00e+00
--------------------------------------------------------------------------------
NSGA-II Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.1167
Total Function Evaluations:
Objectives:
Name Value Optimum
f -3450.18 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 24.523723 0.00e+00 4.20e+01
x2 c 11.437983 0.00e+00 4.20e+01
x3 c 12.300033 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= -0.000245 <= 0.00e+00
g2 i -1.00e+21 <= -71.999755 <= 0.00e+00
--------------------------------------------------------------------------------
ALGENCAN Solution to TP37 Constrained Problem
================================================================================
Objective Function: objfunc
Solution:
--------------------------------------------------------------------------------
Total Time: 0.0291
Total Function Evaluations:
Lambda: [144.00000063 0. ]
Sensitivities: FD
Objectives:
Name Value Optimum
f -3456 0
Variables (c - continuous, i - integer, d - discrete):
Name Type Value Lower Bound Upper Bound
x1 c 24.000000 0.00e+00 4.20e+01
x2 c 12.000000 0.00e+00 4.20e+01
x3 c 12.000000 0.00e+00 4.20e+01
Constraints (i - inequality, e - equality):
Name Type Bounds
g1 i -1.00e+21 <= 0.000000 <= 0.00e+00
g2 i -1.00e+21 <= -72.000000 <= 0.00e+00
--------------------------------------------------------------------------------
Erreur de segmentation
I've been stuck in this problem for a week.
can you tell me how to solve the problem?
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kjyv
commented on June 2, 2024
It's possible that pyOpt has some issues in the ALGENCAN solver (which is not really good for the problems here anyway) that let it crash but the crash is in fcl looking at the stack trace. You might still have a more recent or different version installed but it might also be another problem with fcl. You might have to run a debugger on that part of the code and check what is happening. Please be aware that this framework is not maintained anymore. It did mostly work fine though when I wrote it. Consider it as a starting point with lots of code rather than a black box solution that just does the job for you. I don't have the environment installed for it anywhere to test run it.
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Related Issues (14)
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