Closed wxmerkt closed 4 years ago
In GitLab by @proyan on Jan 27, 2019, 21:28
Deals with #55
In GitLab by @proyan on Jan 28, 2019, 00:20
added 10 commits
loco-3d:topic/refact
In GitLab by @nmansard on Jan 28, 2019, 17:10
What is the current status of this MR? If the work is asleep, should we close it yet, or mark it as in sleep mode?
In GitLab by @proyan on Jan 28, 2019, 18:35
added 1 commit
In GitLab by @proyan on Jan 28, 2019, 18:35
changed the description
In GitLab by @proyan on Jan 28, 2019, 18:37
This MR is done and ready to merge.
I don't know how useful RK4 would be for DDP, since the second order derivatives vastly increase the number of matrix multiplications.
We can approximate as well. However, currently the derivatives are exact (for linear dynamics like DAMLQR) and working.
In GitLab by @proyan on Jan 28, 2019, 19:04
changed title from Rk4 to Rk4{+ --- Ready to merge and waiting for review+}
In GitLab by @proyan on Jan 28, 2019, 19:10
added 1 commit
In GitLab by @nmansard on Jan 29, 2019, 08:42
I find strange that you are introducing complex cost classes here. You should rather have a minimal LQR examples that is stand alone. I don't see the interest of reusing complex code here.
In GitLab by @nmansard on Jan 29, 2019, 08:43
please comment the function. I dont understand what it is doing. What about putting a readable name? What about adding it to the LQR class?
In GitLab by @nmansard on Jan 29, 2019, 08:44
I think this class should go in the main library. We already have ActionModelLQR there. It would be useful to have the DAMLQR as well.
In GitLab by @nmansard on Jan 29, 2019, 08:45
This is useless if remove the cost model, that I advise.
In GitLab by @proyan on Jan 29, 2019, 10:13
This is just to get a random orthonormal matrix. I only added it for the unit test. The source is https://github.com/scipy/scipy/pull/5622/files
In GitLab by @proyan on Jan 29, 2019, 10:51
If we put this in the main library, we have to agree on the convention. To match the second order dynamics eqution in DAM, I am implementing ddy = Ady + By + Cu here. (x = [y dy])
Is that good for you?
In GitLab by @proyan on Jan 29, 2019, 10:53
I can't use the cost models implemented in the main library, because they depend on pinocchioModel. So I needed an equivalent model for the vector space so that the classes in the main library can access the sizes.
In GitLab by @proyan on Jan 29, 2019, 11:08
added 1 commit
In GitLab by @proyan on Jan 29, 2019, 11:10
I added a comment for the function.
In GitLab by @proyan on Jan 29, 2019, 11:15
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In GitLab by @proyan on Jan 29, 2019, 11:15
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In GitLab by @proyan on Jan 29, 2019, 11:15
added 1 commit
In GitLab by @proyan on Jan 29, 2019, 11:16
Done. I removed Vectormodel
In GitLab by @proyan on Jan 29, 2019, 11:18
I need to rewrite the CostModelState here because the class implemented inside the main code is dependent on pinocchio.
In GitLab by @nmansard on Jan 29, 2019, 13:11
name it randomOrthogonalMatrix
In GitLab by @nmansard on Jan 29, 2019, 13:11
Yes I am
In GitLab by @nmansard on Jan 29, 2019, 13:15
I am sorry I do not understand your answer. My point was that DAMLQR should be a very simple class not relying on CostModel to compute the result. The cost should just be l(q,v,u) = qQq + vVv + uUu with Q,V,U three positive matrices. Simple to implement in calc, no need to rely on CostModelState or any other CostModelXXX. Is it not?
In GitLab by @proyan on Jan 29, 2019, 13:19
Ah ok. I'll do that.
In GitLab by @proyan on Jan 29, 2019, 14:25
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In GitLab by @proyan on Jan 29, 2019, 14:25
changed this line in version 7 of the diff
In GitLab by @proyan on Jan 29, 2019, 14:25
added 21 commits
loco-3d:topic/refact
In GitLab by @proyan on Jan 29, 2019, 14:25
Done.
In GitLab by @proyan on Jan 30, 2019, 09:48
Is this MR ok? Should I merge it in devel?
In GitLab by @proyan on Jan 30, 2019, 16:03
added 79 commits
loco-3d:topic/refact
In GitLab by @proyan on Jan 30, 2019, 16:03
marked as a Work In Progress from rbudhira/cddp@cdfd46e06fcfa15504be22808f0959bbc2978fb5
In GitLab by @proyan on Jan 30, 2019, 16:03
changed target branch from topic/refact
to devel
In GitLab by @proyan on Jan 30, 2019, 16:04
unmarked as a Work In Progress
In GitLab by @proyan on Jan 30, 2019, 16:06
added 1 commit
In GitLab by @nmansard on Jan 30, 2019, 17:31
ncost should be the len of the costresiduals. If you dont have residuals, then don't set up a ncost.
In GitLab by @nmansard on Jan 30, 2019, 17:32
data.Fx[:nv,:] = A data.Fx[nv:,:] = B
In GitLab by @nmansard on Jan 30, 2019, 17:33
use v or vq instead of dq
In GitLab by @nmansard on Jan 30, 2019, 17:33
i think you should add a drift term to be generic: a = Ax + Bv + Cu + d
In GitLab by @nmansard on Jan 30, 2019, 17:35
Could you add a disclaimer that this model is not yet heavily tested, and we are not sure that it is the way to go wrt performances?
In GitLab by @nmansard on Jan 30, 2019, 17:36
Doc should go in the first line of the function, as a string.
def randomOM(): '''blablabla'''
In GitLab by @proyan on Jan 30, 2019, 19:03
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In GitLab by @proyan on Jan 30, 2019, 19:03
changed this line in version 11 of the diff
In GitLab by @proyan on Jan 30, 2019, 19:03
changed this line in version 11 of the diff
In GitLab by @proyan on Jan 30, 2019, 19:03
added 2 commits
In GitLab by @proyan on Jan 30, 2019, 19:04
Done.
In GitLab by @proyan on Jan 30, 2019, 19:06
changed this line in version 12 of the diff
In GitLab by @proyan on Jan 30, 2019, 19:06
added 1 commit
In GitLab by @proyan on Jan 30, 2019, 19:06
Done.
In GitLab by @proyan on Jan 27, 2019, 21:26
Merges rk4 -> devel
I added the Linear dynamics and checked the derivatives of the dynamics and costs. The first order derivatives of L and F work.
I implemented the second order derivatives of L as well, however, there is no test yet. 1) The current test, by using the residuals doesn't make sense to me for this integration scheme. 2) I should implement an FD to unittest Lxx, Lxu etc (which should atlleast work for the case of DAMLQR). That is what I am doing now.
In case you wish to merge it now before the school, you could go ahead.
Edit: I added FD on the cost derivatives as well.