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If this is what they’ve done, it’s extremely impressive. Though known in the literature, these are hardly routine techniques like PID and LQG (which mostly won’t work here due to nonlinearity). Much more sophisticated. Still, not defensible.
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A general “tell” of control strategies is beauty. The more elegant it looks, the more symmetry there is to the behavior. Which means many variables are being reduced to a few via symmetry-exploiting maneuvers.
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Contrast with the awkward flailing of trying to learn *any* workable functional behavior. Babies and injured pets often learn weird looking maneuvers this way. But more elegant looking ones are either strong attractors everybody will stumble into, or explicitly trained.
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Hardware — solved Basic control — solved Maneuver control — solved Localized deep learning: 2022 Deep learning entire behavior envelope from humans: 2024 Doing it without human training examples: 2026 Learning the unstable/high-risk bits in simulation: 2028 Akira entity: 2030
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My predictions regarding robotics advance is roughly similar timeline. Do you think independent self-funded research with cheap bots (spot knockoff, robotic arms) could be a valid alternative to big labs and academic path?
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that's what we're doing with the yak rover project... a bunch of us just building rovers with low-cost self-funded research. I've spend about $1000 in parts and tooling for mine so far...
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I'm at fork in the road so to speak. Leverage money from a well paying job towards funding this type of experiments. Or go for a research masters in germany, then figure things out by getting into their lab. I would really appreciate your thoughts here if any.
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A bit late now, will surely join the yak rover. I have a waveshare jetbot with a Jetson nano sleeping around. What's the link to join this collaboration (is it in yak's roam)? I will check yak's website tomorrow.
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