just a repo for tests
🏎️ I’m currently working on Automotive
🌱 I’m currently learning UI and UX quality test on SW tools for Embedded Systems
💬 Ask me about Testing, Optimization, Embedded Systems
ergoCub 1.0 S/N:000
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wqd
dw
dwq
dwq
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ergoCub 1.0 S/N:000
The low level joint control on the arms needs tuning to improve trajectory tracking.
The joint tracking on the arms has up to 4 degrees of error on most joints. This is causing issues with the Cartesian control since the pose of the hands cannot be guaranteed. The right wrist has large errors - up to 20 degrees - though this appears to be a recent problem that we didn't observe a month ago.
We recorded the tracking error for the joints tracking a joint-level trajectory:
We then recorded the joint tracking when running a Cartesian controller. The errors are much larger. Cartesian feedback is used to try and make sure the hands stay together when grasping with 2 hands, but since the low level joint tracking is innacurate this is causing the robot to overcompensate:
Here is a video of the 2-handed grasping before ICRA 2023 and without Cartesian feedback on the position error of the hands. The ergoCub drops the object because the hands do not move together precisely because of the low-level joint tracking problem:
Here is a video after where feedback on the hand positions was used to try and keep them together. The robot overcompensates because the joints are not tracking accurately and the error on the hand poses increases instead of decreasing:
Myself @Woolfrey and Vignesh @vigisushrutha23 need accurate Cartesian control to demonstrate research in bimanual manipulation as part of the ergoCub project.
High-level feedback control to correct the pose error of the hands is also not possible unless the underlying joint tracking can be guaranteed (as shown in the video).
@xEnVrE : FYI
iCubBielefeld01 S/N:006
uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
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ergoCub 1.0 S/N:000
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ergoCub 1.0 S/N:000
xxx
xxxx
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iCubBielefeld01 S/N:006
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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ttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttt
ttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttt
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ergoCub 1.1 S/N:001
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None
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ergoCub 1.0 S/N:000
The low level joint control on the arms needs tuning to improve trajectory tracking.
The joint tracking on the arms has up to 4 degrees of error on most joints. This is causing issues with the Cartesian control since the pose of the hands cannot be guaranteed. The right wrist has large errors - up to 20 degrees - though this appears to be a recent problem that we didn't observe a month ago.
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ddd
dd
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ergoCub 1.0 S/N:000
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iCubBarcelona01 S/N:013
bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb
bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb
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ggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggg
gggggggggggggggggggggggggggggggggggggggggggggggggggggggggggg
ggggggggggggggggggggggggggg
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ergoCub 1.0 S/N:000
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ergoCub 1.0 S/N:000
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ergoCub 1.0 S/N:000
ooooookkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
okkkkkkkkkkkkkkkkkkkkkkkkkk
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ergoCub 1.0 S/N:000
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
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iCubBielefeld03 S/N:019
yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy
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None
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None
The low level joint control on the arms needs tuning to improve trajectory tracking.
The joint tracking on the arms has up to 4 degrees of error on most joints. This is causing issues with the Cartesian control since the pose of the hands cannot be guaranteed. The right wrist has large errors - up to 20 degrees - though this appears to be a recent problem that we didn't observe a month ago.
We recorded the tracking error for the joints tracking a joint-level trajectory:
We then recorded the joint tracking when running a Cartesian controller. The errors are much larger. Cartesian feedback is used to try and make sure the hands stay together when grasping with 2 hands, but since the low level joint tracking is innacurate this is causing the robot to overcompensate:
Here is a video of the 2-handed grasping before ICRA 2023 and without Cartesian feedback on the position error of the hands. The ergoCub drops the object because the hands do not move together precisely because of the low-level joint tracking problem:
No response
ergoCub 1.0 S/N:000
No response
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None
xxx
x
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None
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
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ergoCub 1.0 S/N:000
Problema 1,2,3 ...
Degli problema 1:
Dettagli problema 2:
Contesto ulteriore
Urgenza con prioritá 2/5.
iCubBarcelona01 S/N:013
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ergoCub 1.0 S/N000
ciao
dw
dwe
dw
ergoCub 1.0 S/N:000
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iCubErzelli02 S/N:036
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ergoCub 1.1 S/N:001
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None
dfghfjgkjhlh
gddh
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iCubGenova03 S/N:020
aaaaaaaaaaaaaaaaaaaaaaaaaaaaa
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iCubBarcelona01 S/N:013
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ergoCub 1.0 S/N:000
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ergoCub 1.0 S/N:000
xxx
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None
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ergoCub 1.0 S/N:000
xxx
xxx
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ergoCub 1.0 S/N:000
The low level joint control on the arms needs tuning to improve trajectory tracking.
The joint tracking on the arms has up to 4 degrees of error on most joints. This is causing issues with the Cartesian control since the pose of the hands cannot be guaranteed. The right wrist has large errors - up to 20 degrees - though this appears to be a recent problem that we didn't observe a month ago.
We recorded the tracking error for the joints tracking a joint-level trajectory:
We then recorded the joint tracking when running a Cartesian controller. The errors are much larger. Cartesian feedback is used to try and make sure the hands stay together when grasping with 2 hands, but since the low level joint tracking is innacurate this is causing the robot to overcompensate:
Here is a video of the 2-handed grasping before ICRA 2023 and without Cartesian feedback on the position error of the hands. The ergoCub drops the object because the hands do not move together precisely because of the low-level joint tracking problem:
No response
None
No response
No response
No response
No response
ergoCub 1.0 S/N:000
The low level joint control on the arms needs tuning to improve trajectory tracking.
xxx
No response
No response
iCubGenova03 S/N:020
ooooooooooooooooooooooooooooo
No response
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No response
None
ddd
ddd
No response
No response
ergoCub 1.0 S/N:000
The low level joint control on the arms needs tuning to improve trajectory tracking.
The joint tracking on the arms has up to 4 degrees of error on most joints. This is causing issues with the Cartesian control since the pose of the hands cannot be guaranteed. The right wrist has large errors - up to 20 degrees - though this appears to be a recent problem that we didn't observe a month ago.
We recorded the tracking error for the joints tracking a joint-level trajectory:
We then recorded the joint tracking when running a Cartesian controller. The errors are much larger. Cartesian feedback is used to try and make sure the hands stay together when grasping with 2 hands, but since the low level joint tracking is innacurate this is causing the robot to overcompensate:
Here is a video of the 2-handed grasping before ICRA 2023 and without Cartesian feedback on the position error of the hands. The ergoCub drops the object because the hands do not move together precisely because of the low-level joint tracking problem:
Here is a video after where feedback on the hand positions was used to try and keep them together. The robot overcompensates because the joints are not tracking accurately and the error on the hand poses increases instead of decreasing:
Myself @Woolfrey and Vignesh @vigisushrutha23 need accurate Cartesian control to demonstrate research in bimanual manipulation as part of the ergoCub project.
High-level feedback control to correct the pose error of the hands is also not possible unless the underlying joint tracking can be guaranteed (as shown in the video).
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