[munificent]

I don't have any expertise in this field, but I expect sailboat training simulations would be much harder than aerial drones because of the underlying physics involved.

I'm sure flight simulations have to deal with some amount of fluid mechanics and turbulence to get an accurate simulation, but I suspect it's fairly simple and you can mostly model it accurately enough using Newtonian physics.

But for sailboats, the entire system relies profoundly on the interaction of two separate fluids with a single body and turbulence and viscosity are deeply interwined in making the boat go. Not to mention that the sail itself is a flexible deformable surface.

Seems like an absolute simulation nightmare.

[talldatethrow]

As a sailor, you're giving sailors a bit too much credit. Those things all matter, but to say that the average sail boat racer is even optimizing for all those things efficiently at once is a huge stretch. A lot of sail boat racing is strategy and properly performing the basically in a hostile environment. If you could ensure great strategy based on learned data, and immaculate execution based on properly tuned controls, I think you'd win easily.

[OnlineGladiator]

I don't think GP is saying that sailors take all of those effects into account constantly, so much as he's saying a useful simulation would be monstrously difficult due to the underlying physics.

I've made robot models in the past, but never for anything involving water (although I actually have done physics simulations with water but nothing with robots). I don't know anything about sailing and I'm definitely not an expert at building simulations, but I can grok what GP meant and I agree with his assessment.

To give a rough analogy - it would be like trying to learn how to be a racecar driver on a videogame with simplified physics. There are professional drivers that use simulators and iRacing (or Assetto Corsa or a handful of other games) but none of them are training on Need for Speed, and it's because the difference is so stark you're actually handicapping yourself instead of learning how to drive. You need the simulation to be close enough to reality before it starts to become useful.

[taneq]

A simulation doesn’t necessarily need to be remotely physically accurate to be useful, as long as the simulated behaviour is qualitatively similar to the real thing. For sailing a small boat, I’d imagine the important things would be the shape of the sail and the heel of the boat for a given apparent wind, presented to whatever sensors your sailbot is using. For the water’s surface, random semi-regular perturbation (sum of sine waves) would be fine, and something similar (or maybe a random walk) for wind direction and strength.

For this kind of real-world robotics, you can’t optimise in any academic sense so you just have to go for effective and robust.

[bodangly]

Well, for the drones, we did base things off ground truth captured in a mocap lab, and this helped the models significantly. There always will be a jump from simulation to real world, but the smaller you make that jump the quicker you’ll have a functioning vehicle. Without that, you can spend a ton of time (wasted) in simulation when the real world is substantially different. I’m sure a sum of sine waves would get you somewhere, but only so far. To me this is a difficult problem and I think it might be best to do most development in a real world environment.

[taneq]

I was just talking about sailboats specifically, where the external forces are highly unpredictable and similar in magnitude (albeit hopefully a fair bit smaller!) than your control authority over the boat.

The work you did on drones sounds very cool and in that scenario (high powered motors, crazy nonlinear dynamics, relatively small external perturbation, at least from how you described it?) I don't doubt that ground truthing your simulation using mocap data made a huge difference.

[munificent]

> as long as the simulated behaviour is qualitatively similar to the real thing.

My point is that I suspect that unless you have a very sophisticated simulation, it won't be.

> I’d imagine the important things would be the shape of the sail

The shape of a sail is itself a very complex thing to model and simulate. I'm not even a real sailor and I'm already thinking about camber, twist, and luffing. When sailing upwind, the sail is functioning like a wing using lift. When sailing downwind, it's relying on drag. Points in between use a mixture. This implies that turbulence and stall must be simulated at some level of fidelity.

If you've got a mainsail and a jib, then you have to worry about the slot effect and one sail blocking the wind of the other.

> and the heel of the boat for a given apparent wind

Not just heeling, but weather helm, leeway, drag, displacement, and how those interact.

[ioseph]

Agree, I imagine just maxing VMG on the fly as conditions change is something a computer could already outperform humans easily.

I've wanted to make a simple sailing game for a while now but found it very hard to actually get something that feels right and compared to other activities there doesn't seem to be great resources on all the different parts of the physical system (in terms of Math).

[munificent]

> If you could ensure great strategy based on learned data

That's my point. If your learned data is coming from a simulation that doesn't model actual sailboat fluid dynamics, you've learned little.

A robot that learned to sail by studying a hollow cube floating in a bathtub full of marbles is not going to be able to make an actual sailboat do anything useful out on real water.

[bodangly]

Yes getting timestamped and synchronized ground truth to build/verify your model will be quite challenging for something like this. For the drones we just took them to a mocap lab, and races are inside so we had the luxury of assuming 0 wind. The only remotely tricky part is handling ground effect from the props.