[mikestew]

Ever wondered why in millions of years nature didnt evolve a LIDAR equivalent and most species use passive vision?

Because it compensated for poor sensor hardware with a processing unit and software that we have thus far been unable to even come close to replicating? Granted, solve that, and we’re just a few years away!

[candiodari]

The problem with that is that LIDAR is a sensor that is so unlike human perception humans completely misjudge what it's capable of. After an accident humans refuse to believe that the sensor really didn't see it coming, which of course is a big problem later in court. Sonars have the same problem. There's things those sensors can see that humans just can't but in the case of Lidar, only in specific planes (so, for example, it just doesn't see things that "point" at the sensor. It just doesn't see stairs or even an abyss, even at close range). Sonar has similar problems. It sees everything everything everything ... as long as there is a whole lot of consistent nothing surrounding it. When there is structure on the sea floor, sonar is useless near it. When there is a ship on the surface accelerating, the eddy currents create a region around, behind and below the ship where the sonar is blind. And near the surface, sonar is useless. The more wind, the deeper the problem goes. In a storm, it can be 10 meters and more. People with decades of experience for some reason seem to outright refuse to believe that.

People seriously misjudge the limitations of these sensors, and this leads to accidents.

Better to use cameras, which have almost exactly the same issues humans have (e.g. bad vision in low light, limited view, "blind" angles near corners, bad optical performance near the edges, ...), which will lead to "understandable" mistakes.

Nobody will understand if a LIDAR misses a beam sticking out of a truck in front of you (which would be expected behavior: such a thing is essentially invisible to LIDAR) and impales the person sitting in the passenger seat on it.

Or the Tesla fuckup. Failing to see the difference between front and back wheels of a large truck and 2 cars. Then decapitating the driver by driving in between the 2 sets of wheels at high speed. That's a typical LIDAR issue.

Sooner or later LIDAR will decide that just driving off an abyss is the best solution to a simple traffic situation (because LIDARs see abysses everywhere, so they use algorithms that assume abysses don't exist).

I've seen LIDAR controlled robots drive into tables "decapitating" (sort-of) themselves, because it only saw the feet of the table, looking at the data, and coming to the conclusion ... yep ... it was a perfectly understandable mistake. That robot also threw itself off the stairs. Again ... tough to fault it for that, as it saw the stairs as pretty much the same thing as a stick lying on the floor. Afterwards looking at the data, that was a perfectly reasonable conclusion.

We lost the robot to the stairs. I was looking at it making that decision. Why ? You see it move, and you're automatically assuming "surely it's not going to go for the hole in the staircase". And then it decides on a solution. Boom. And yes, I pressed the emergency stop button. Doesn't help much if the robot is already falling.

[Ntrails]

> Better to use cameras, which have almost exactly the same issues humans have

Surely, he cries, the argument is to use both and simply apply use some kind of likelihoods/confiendence in the output to combine them?

[franciscrick1]

You say this ironically, and yet every indicator points toward this happening in the next 5-10 years!