Sikorsky’s autonomous helicopter tech is ready for takeoff
theverge.com
theverge.com
i've just recently finished peter watts "freeze frame revolution" of the sunflower cycle, where the gate-building spaceship eriophora is mostly on its own for thousands of years while the crew sleeps, guided by an AI called "the chimp".
-- spoilers --
one of the key ideas in this book is that the ships AI - the chimp - is not advanced at all, with a synapse count of roughly the chimp. anything more intelligent would get unstable and develop its own motives, so the original builders constructed it to be comparatively dumb and thus stable, predictable and deterministic (the humans are woken up only in case something unexpected happens which requires more creativity and brainpower).
I wonder whether a hybrid approach is the future, since in some tasks neural networks are just far better than anything we have. If the only tasks of the neural network is to estimate/classify some sensor-input and is trained in a purely supervised setting, the "right thing" for the neural network is still pretty well defined and rigorous testing should be possible (simple tasks can be very complex to implement). Then, interpretable, high-level reasoning could be solved by old-school coding (and maybe verifying).
This is not possible with end-to-end training.
But I am not sure what they mean, normally neural network (and their training) is purely deterministic. It's not that they are just very good at rolling a dice.
I am not into this stuff (autonomous, "intelligent" systems, more the data-analysis guy), but I would use neural networks for simple to define, hard problems that involve a lot of noisy data (where some kind of accuracy on some test-set is a well-defined metric) and then build a higher-level reasing system by hand.
Doesn't every component in an aircraft have a random chance of failure? There's even a name for one critical component, the Jesus nut.
I don't really get the interpretable argument. I think what you want is to verify it to a reasonable degree.
Two things;
1) This might be theoretically true, but Boeing and other aircraft manufacturers monitor data on every component at a very fine-grained level and they use inspections to predict what will go bad and when. They're even adding real-time capabilities to it so that parts are replaced immediately after a flight if imminent failure is predicted; https://www.boeing.com/commercial/aeromagazine/articles/qtr_...
2) The core issue over here isn't that a component can fail. The issue is that when it fails can we trace the error and forestall it in the future? If the error is something that's unreplicable and unpredictable then that's quite literally impossible and it makes the machine by its very definition untenably unsafe as you don't know when or why it won't work.
Someday neural networks will become a part of safety-critical systems, but this generation of neural networks probably won't be it.
to 1). Neural networks are code, they are always 100% the same if you ship it. So you can test them way more thoughly than some equipment, which (i hope) would allow you to minimze the chance of failure to a reasonable degree.
to 2) "you don't know when or why it won't work." I think a fundamental disagreement lies here. I am convinced that this is not possible with these complex function approximators, where we just optimize them until we are happy. If we adopt a thinking like above, we can retrain the networks with these additional inputs, adjust our notion of robustness and think whether there's a flaw in our statistical assumptions.
But these are just random thoughts. I am in touch with people working in healthcare with this stuff, so there's some exposure to these kinds of problems. But I have never read any work discussing these issues or really reflection whether my reasoning is actually sound.
Maybe I'm wrong and we can somehow make them interpretable in a sense that is actually relevant to verifying them.
Most of this is because helicopters are complex machines (you're spinning really big blades pretty fast. Then using the blades + bearing to also lift the weight of the helicopter + more. Oh and you're changing the pitch angle of the blades. Oh you mean changing the pitch angles of the blades WHILE THEY GO AROUND...) and any failure in any of these parts is usually fatal so they have to be built and maintained to a very high degree of reliability.
Airplanes are much simpler (the spinning propeller attached to an engine is one part. The wing generating lift is another part. the flight controls are yet another part) and have more opportunities for redundancy ( a wing has multiple spars, and is attached to the airplane with many bolts. All helicopter blades meet in one hub, which is attached on one axis).
Combine that with aircraft scaling up more (you can build 500 person aircraft, but only 20 person or so helicopters), going much faster (a 120 dollar/hr propeller plane will outrun many/most helicopters) and the cost to go a given distance by plane will always be much cheaper than a helicopter.
Also, helicopters are generally used for other purposes than planes. Transporting thousands of men thousands of kilometers is probably not a job for helicopters but that does not imply that helicopters are useless.
I would agree with you operating a helicopter will always be expensive. I don't anticipate autonomous helicopters to be price competitive with something like cars. People pay the premium for vertical flight to gain the benefits of vertical flight. In addition, I'm pretty sure that given the high fixed price, that market would rather pay more to get a premium product rather than accept an inferior product (e.g. insufficient range, speed, flight time, safety, etc). I was more saying making helicopter flights marginally cheaper will make said flights marginally more available to more people.
There might be game changers down the line. For example, Sikorsky has a lot of experience with experimental control systems like hybrid helicopters that may reduce operational expenses, and if they can prove SARA/derivatives are as reliable or better than a human pilot and convince the general public/unions to fly without a pilot, they might design helicopters that are more maintenance-oriented. But as with all things, it's more important to make sure new innovations are deliverable and provably progressive.
If he stayed in Russia the course of human history might have been very different ... if he was developing all that technology for the USSR... and not USA.
tell me about boot strapping!! :
"In 1923, Sikorsky formed the Sikorsky Manufacturing Company in Roosevelt, New York.[36] He was helped by several former Russian military officers. Among Sikorsky's chief supporters was composer Sergei Rachmaninoff, who introduced himself by writing a check for US$5,000 (approximately $61,000 in 2007).[37] Although his prototype was damaged in its first test flight, Sikorsky persuaded his reluctant backers to invest another $2,500. With the additional funds, he produced the S-29, one of the first twin-engine aircraft in America, with a capacity for 14 passengers and a speed of 115 mph.[38] The performance of the S-29, slow compared to military aircraft of 1918, proved to be a "make or break" moment for Sikorsky's funding."
Imagine it didn't. Literally the outcome of WWII could have been very different.
Of course "what if's" dont count. Still fascinating to me how much he's accomplished 100 years ago!
Here we are today burning 100's of millions in cash of investors money with "0 results" (really). lol
Mikhail Kalashnikov wanted to design agricultural equipment because he wanted to help prevent famine. Who knows if he would have been any good at it but that door closed on June 22 1941.
It's hard to say what would have happened had history been different.
I have serious doubts about this. His talents might be lost for humanity completely. Post-revolution and before WW2 there were a lot of constructors and engineers who were prosecuted, displaced or even worse by the Soviets.
The wikipedia says "After the Bolshevik revolution began in 1917, Igor Sikorsky fled his homeland, because the new government threatened to shoot him." (the citation link is broken, unfortunately).
This reminds me of Sergey Korolev's history. He was basically the father of Soviet rocket-building. He has survived the purges by pure luck. The leaders of his institute were executed, he was tortured to get the confession, lost his teeth, went through the gulag and got back. How many of these talented people ended up being not so lucky is hard to imagine.
Even the work results might not have protected them. For example, take the chief engineer of T-34 engine https://en.wikipedia.org/wiki/Konstantin_Chelpan. He got awarded for the invention, arrested and executed the next year, and then rehabilitated a few years later. There were so many stories like these.
1: https://en.wikipedia.org/wiki/Cultural_Revolution#Education
No they are not that hard to fly. A bare-bones helicopter with nothing more than the minimum parts to qualify as a helicopter is indeed an unsteady beast. But such helicopters are rare, used mostly for training purposes. Modern machines, even ancient ones, have things like gyroscopes to take much of the load off the pilot. And autopilots really do work (auto, not autonomous). They can hold a steady heading/alt. Feed them data from a radar altimeter and they can hover like a rock.
The computers can fly the aircraft, they can literally make it move as needed, but that is a totally different problem than deciding where to move the aircraft. The pilot's job is making the judgement calls necessary to keep the aircraft safe. Show me a computer than can determine whether an approach is safe enough to execute, whether the weather en route is acceptable. Show me a computer than an judge which path to take to avoid carrying an unsteady slung load over someone's head.
That's not good, right?
There are legends in AF helo communities about entire crews falling asleep during long hovers. (The anti-submarine helicopters have to hover in place while dipping their sonar into the water.)
> The ships hung in the sky in much the same way that bricks don't.
https://aviation.stackexchange.com/questions/35764/are-helic...
To your first point-and I think you hit it but I wanted to emphasize-some helicopters are hard to fly, some mission sets are more difficult than others; hovering with a 30 knot tailwind in a $32 million dollar aircraft with SCAS and AFCS is still a pain in the ass especially when it's low light and you're on goggles...but I guess the AI wouldn't need to be aided, so call that a win.
Lol. Helicopters are not 747s. They operate very locally and do things that are not as generic as approaching SFO in marginal weather. A helicopter has to change its operations in reaction not to measured weather, but to the specifics of individual trees. Show me a computer that can take the input: "That tree looks like it is about to fall over" and decide whether to continue a rescue or give up and negotiate a new approach. SAR pilots do that daily.
Considering the way you lambaste ideas that it is becoming increasingly evident you don’t fully understand, I’d be interested in your credentials.
I suspect you have not tried hovering in a helicopter.
> autopilots really do work
There are actually very few autopilots that can hover. Not just because it's technically hard (the soviet Kamov helicopters could maintain hover back in 1980's), but also because of the certification requirements.
If a DJI drone hits a tree it's not a big deal. The story is very different when a helicopter does it.