New physics sim can compress training times from decades into hours

> It has a camera and is supposed to avoid all these things, but it straight up never works. I have a nightly routine

Try running it in daylight. Mine from Eufy is similar, has a flashlight, but good ambient light is superior. Still, the cameras and image recognition is extremely flaky imo (the Ai parts), whereas the LiDAR for navigation is absolutely spectacular. Even if you move furniture around and drop it randomly in a different room it always finds its current location in less than a minute.

I wonder why there haven't been more effort into roller-less vacuums. Shop vac style, just air, no exposed moving parts other than wheels.

For all of us who have no carpet, and pets that shed hair that tie up rollers, it would make perfect sense.

Full disclosure: I left the company that became iRobot well before the Roomba, so I have zero insider knowledge.

But if you're familiar with Rod Brooks' public work on the "subsumption architecture", the Roomba algorithms are pretty obvious.

Early gen Roombas have 3 obvious behaviors:

1. Bounce randomly off walls.

2. Follow a wall briefly using the "edge" brush.

3. When heavy dirt is detected, go back and forth a bit to deep clean.

Clean floors are an emergent result of simple behaviors. But it fails above a certain floor size in open plan houses.

Later versions add an ultra-low-res visual sensor and appear to use some kind of "simultaneous localization and mapping" (SLAM) algorithm for very approximate mapping. This makes it work much better in large areas. But you used to be able to see the "maps" from each run and they were horribly bad—just good enough to build an incredibly rough floor plan. But if the Roomba gets sufficiently confused, it still has access to the old "emergent vacuuming" algorithm in some form or another.

The newest ones may be even smarter, and retain maps from one run to the next? But I've never watched them in action.

I really like the old "subsumption architecture" designs. You can get surprisingly rich emergent behavior out of four 1-bit sensors by linking different bit patterns to carefully chosen simple actions. There are a couple of very successful invertebrates which don't do much more.

I can totally spend time watching them, rooting for them to randomly (well, one is the random pinball type, one has some kind of camera and makes nice straight lines) pick up a piece of dirt in the middle of the floor. It’s kind of the same feeling as watching a bunch of puppies play.

Furbies for adults.

(But not that "adult", thank goodness.)