Reading through the paper, it's pretty remarkable how well the control works with how many dynamical approximations you guys make! The A and B matrices are way simpler than I'd expect, and I'm surprised you don't get more side-slipping with the square friction "cone". Throwing the constraints into the cost function was smart too - well done!
I have read your paper "Dynamic Locomotion in the MIT cheetah through convex MPC", it is great. However, I did not understand how you measured/estimated the velocity of the COM (which is one of the variables of the State Space). Can you please explain?
Great Job, but your paper is a bit cryptic. in the MPC formulation what is x0, how is expressed what it is inside. I find great difficulties to understand how to implement expression 32 ( the equation g = 2B'L(Ax0 -y). y was never mentioned before too, what is it?
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Reading through the paper, it's pretty remarkable how well the control works with how many dynamical approximations you guys make! The A and B matrices are way simpler than I'd expect, and I'm surprised you don't get more side-slipping with the square friction "cone". Throwing the constraints into the cost function was smart too - well done!
The guy with the stick there to kill it if it goes rogue?
That is so impressive... 😮
I don’t know why but the side step seemed extra impressive.
the human wear a mace if ever the robot atempted to raise
Meet the new boss.
No robots were harmed during the making of....... Oh wait!.. 3:10
I have read your paper "Dynamic Locomotion in the MIT cheetah through convex MPC", it is great. However, I did not understand how you measured/estimated the velocity of the COM (which is one of the variables of the State Space). Can you please explain?
Why was the leg movement design changed from the previous version ?! is it more efficient or just because it is more adaptable?
I hope MIT will make it all "open". They are famous for open research.
yes if your enought rich its fully open
I can imagine an MIT student just riding this to class
Great Job, but your paper is a bit cryptic. in the MPC formulation what is x0, how is expressed what it is inside. I find great difficulties to understand how to implement expression 32 ( the equation g = 2B'L(Ax0 -y). y was never mentioned before too, what is it?
USPS ad.
Is this code avaible publicly?
I wonder why the legs are backwards compared to animals?
too much
Boston Dynamics copy.