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Very cool

What are the optimum value of coefficients for alpha ,Beta &gamma for computing of torque of the arm in general matrix please?

this video was randomly recommended to me but as i plan to work in the medical science field in the future i will watch it

brilliant lecture! Thank you Dr. Lei!

Also cover different control techniques.. for actuator control in robot manipulator and also trajectory control based on kinematics or dynamics of the system.

This is a well done video, thank you. 👍

why did this gedt reccomended to me!?

Can you provide the slides for study?

The idea that certain observables are only noticeable with the passage of time is an interesting starting assumption for filtering out all kinds of dead ends, perhaps even reductionism sponsored theories as well. The generalization of this might be that the effects being observed after the passage of time infers that constraints are as well, as with say the liquid chemical reaction that oscillates between colors. Each state sets up the constraint for the next state, and vice-versa. Or other systems may lock into a self-generated attractor, etc, as like tbe case of a knot, or perhaps more loosely a vortex. It seems that this self-constraining ability or tendency, is the “dark matter” side of dynamics. Generalizing further, we get into harmonically complex systems or perhaps manifolds of changing change. But there is time, still staring us in the face. How objects self-assemble or even how goods get factory assembled, seems to be related to this, as sequence is fundamental to the unfolded result, be it assembled object, algorithm or recipe. I like the fuzzy space between objects as hard little atoms, and metaphysical objects, like time and potential energy, or least action relational abstractions, for example. But time and evolving constraints that “emerge” seem under-appreciated. Language and symbols and maps are created to point to something we labeled “next time around”. We have to experiment with duplicated circumstances in the future, in order to detect the “intention” or phenomenon which we witnessed in the past, armed with new tools or instruments. So the “goal” or subassembly of a system is not observable until one can take it apart and analyze it in the future, so in effect we must travel toward in time a second time, in order to properly contextualize a phenomenon, because not only is it’s assembly graph “living in time” or “spread across time” but so is our assembly graph, and so are our thoughts about the original. So this is kind of like the logical limits of light cones and relative sequences tied to evolution of objects and ideas, without invoking relativity per-se. I suspect I am butchering a beautiful idea. It’s more like you can’t get there from here directly kind of thing, you have to duplicate the circumstances to detect an organizing principle, after forming a hypotheses, it’s never deductive without hypothesis as Newton insisted. This may be closer to the reason why my wise friends celebrated the assembly theory work and its method, they like Platonic modes over the Cartesians.

This idea of increasing self-constraints becoming manifest as additional building blocks are added, seems under-appreciated at large. There is a new theory called assembly theory which focuses on the history of assembled molecules and perhaps extended to objects, and then say the object defines its own complexity class and can can be ranked based on the necessary components that went into it. The last high point was witnessing the new pattern derived from chemical light spectra of molecules which are then analyzed using the new method in order to rank each compound in complexity. Compounds above a certain ranking number were consistently proven to be ether from life or causally downstream from life, and were confidently detected in mass spectrometry and other types of instruments such as Magnetic Resonance Spectroscopy. NASA funded them to find life on other planets using their new method of molecule classification, since this is very convenient since spacecraft already have mass spec instruments onboard. Other deepest of deep experts I follow suggested there is a rarely expressed deeper Epistemology present in their work, at the interface of chemistry and biology, which unfolded, may return science back to the path away from reductionism towards more platonic “top-down organizing principle driven” species of method, and are applauding it as such, but I, while enthusiastic of the prospect, am still trying to tease out exactly what they meant and how it was expressed in their method. See Assembly Theory on TH-cam

On orbits and initial condition assumption, despite different planetary systems existing, the question seems related to the quantization of harmonic systems. That is, if new harmonically related restorative forces appear after the system has been largely settled, similar to the wave theory of the atom, We’re not into your values of the wave around the circle are inherently unstable and settle into integer values. Is there an attractor which maintains the status quo of the orbits to some degree I would make it a kin to painting yourself into a corner. Once you’ve committed to a design, the design set tends to be self reinforcing due to established constraints not present earlier.

Trying again to cross post a video and a paper related to dynamical field theory. Since I don’t see my comment with links appear here in comments, I will just give titles to insure at least the idea is posted; just Google the titles and you will find a nice echo of your work. TH-cam: Can We Build an Artificial Hippocampus? ARXIV paper: RELATING TRANSFORMERS TO MODELS AND NEURAL REPRESENTATIONS OF THE HIPPOCAMPAL FORMATION The overlap here, with dynamic field theory is quite impressive. And I am seeing convergence of convergences of theory, and perhaps this is the object which is coming into view, the convergence of convergences as a universal method. The novelty I see here is that Euclidian or periodic space is learned rather than hardcoded. Please watch the video and you will see it appears very similar in other respects to dynamic field theory. The terrain grid of place versus event comes to mind prominently. The paper goes even further, where they claim to have used the HIPAA campus model to improve the transformer model Now I am wondering if since space can be discovered, different spaces can be discovered like complex numbers, or Riemannian manifolds. There is already talk of a tours manifold “hosting” positional space in animal brains. Perhaps the ultimate abstraction is to treat convergence of a simple model, as simply a new stimulus in a greater space abstraction. I could picture this cascaded, forming a manifold of models. I love your work here. It was so pure and simple without adding ornamentation that it allowed the main ideas to come through without interference. i wish you luck on your discovery path, your work is great, and hopefully this post will brighten your holidays. Merry Christmas and happy new year!

Wonderful resource for my PhD Studies in Decision Making

thank you so much!

can you give me humanoid robot with 17DOF dynamic modeling

gg

hello I'm not good at English but i want to contact you to ask some questions. How can i contact you?

It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with primary consciousness will probably have to come first.

Thank you! Here’s a little something for you: th-cam.com/video/TQUTGgZbnMg/w-d-xo.html

Chinese ，please

z82ik vur.fyi

wow. that was very enlightening I must say. I really thought I had seen it all with DFT.

[AI AI AI AI AI] Good Video, I understood something for a change

thank you that you make this lecture publicly available

Thanks for your lecture, could you please upload next lectures in highest resolution.

I was curious about the comment at 42:40 about the DFT approach to coupling instabilities and an earlier approach in analog computing. Would you say that this belongs in some kind of canonical ancestry of DFT? I would be curious for a reference for these issues in analog computing if you wouldn't mind? It's about time these videos got a lot more views than they currently do. I am a big fan.

I can't believe I'm only just finding these lectures now. I remember being in the audience for this. Really impressive work.