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Indeed, it's unclear if anyone has yet to develop a path planner that can overcome "the freezing robot problem". Even with perfect perception performance, which
by im_down_w_otp 7y ago
Indeed, it's unclear if anyone has yet to develop a path planner that can overcome "the freezing robot problem". Even with perfect perception performance, which doesn't exist, the path planning to deal with congested environments is an unsolved problem, and the path planning to deal with ambiguous multi-modal intent might be an unsolvable problem.
To add insult to injury, the manner in-use today of modeling humans as essentially just another kind of dynamic object breaks down extremely quickly once humans are normalized to the presence of autonomous robots. The humans change their own behavior model to achieve their own objective function. They're not dynamic objects, they're learning objects, and now your AV models (which will include human interaction and reaction behaviors on purpose if you're it right and on accident if you're not) breakdown along an entirely new longitudinal axis.
I think the AV market fundamentally broke when GM acquired Cruise for $1B seemingly out if nowhere.
1) Because the reality is that the DARPA Urban Challenge result was not assuredly generalizable, and it may be the case that there's still basic science to be done before the domain is just better, cheaper sensors & high-performance compute away from being productionizable.
2) It's not at all clear that deep learning is really iterating toward a solution to this problem either, but the improvements to methods and hardware have produced the ability to make very compelling demos, that even the purveyors of themselves might believe in, and show iterative improvements on the previous result, thus fueling more investment into something that isn't even known to be possible.
3) But, none of that would matter if GM hadn't decided to make a power move in throwing $1B at an acquisition and in one fell swoop turned an early stage unproven scientific research market into a super, super frothy capital market where it looked like anybody at any moment could be a unicorn without any clear reason or any fundamentals.
Investors went insane and the expectations and promises followed them.
- tlarkworthy 7y agoWe have multi player poker breakthrough so it seems possible. I don't think planning is the core issue, I think that's solvable in time, it's the hardware and reliable general perception that is the blocker
- rimliu 7y agoIn poker, the computer knows, that none of the players will suddenly start playing chess instead of poker. On the road, the number of possible situations is way way way bigger.
- sandworm101 7y agoNot just bigger. Bigger can be fixed with more cpu time. It is a fundimentally different problem. Nobody has a good theoretical answer even with infinite cpu time. I say this while on a car ferry. Getting on this boat required me to navigate several strange road markings and obey a half-dozen hand gestures from staff, including several that were contrary to the painted lines. No AI is even contemplating car ferries.
- ghaff 7y agoRight. And, sure, that's an edge case for most people. But even if such edge cases only crop up every now and then, you're now at the difference between a reliable automated door-to-door system and one that can drive you around most of the time but every now and then forces a hopefully sober/licensed/competent driver to get behind the wheel to take some actions. That's a huge difference. Maybe you can address it with some sort of remote OnStar-like system but now you're forcing a remote operator to jump into an unknown context and take actions that were too hard for the AI.
- AnimalMuppet 7y agoIt's not just car ferries. Accident scenes and construction zones sometimes require you to obey hand signals and ignore road markings. There aren't many car ferries around where I live. But there's plenty of construction...
- sandworm101 7y agoEver area had its little thing. They may be edge cases individually but edge cases, as a group, must be planned for.