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A Short Introduction to Automotive Lidar Technology

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Re: A Short Introduction to Automotive Lidar Technology

#11
post #2

Related: https://www.viksnewsletter.com/p/teslas-big-bet-cameras-over...

Waymo tried cameras-only recently as a research project.[1][2] They seem to do about as well as Tesla, which they don't consider good enough.

[1] https://www.forbes.com/sites/bradtempleton/2024/10/30/waymo-...

[2] https://arxiv.org/pdf/2410.23262

Re: A Short Introduction to Automotive Lidar Technology

#12
post #11
post #2

Related: https://www.viksnewsletter.com/p/teslas-big-bet-cameras-over...

Waymo tried cameras-only recently as a research project.[1][2] They seem to do about as well as Tesla, which they don't consider good enough. [1] https://www.forbes.com/sites/bradtempleton/2024/10/30/waymo-... [2] https://arxiv.org/pdf/2410.23262

One of the cool thing about the Waymo Driver is that it can be configured to work with different degrees of quality depending on the sensors available. In a low risk environment (e.g. closed to humans) like operating forklifts in an autonomous warehouse, it would work fine with just cameras. Waymo hasn't been very boastful to date, but some of the capabilities are hinted at in this interview: https://www.youtube.com/watch?v=d6RndtrwJKE

Re: A Short Introduction to Automotive Lidar Technology

#14
Here's an interesting "lidar gem" from Hacker News a few years ago:

https://news.ycombinator.com/item?id=33554679

Lidar obstacle detection algorithm from a Git repo leaked onto Tor

This is a drivable region mapping (obstacle detection) algorithm found in what appears to be a git repo leaked from an autonomous vehicle company in 2017. The repo was available through one or more Tor hidden services for several years.

The lidar code appears to be written for the Velodyne HDL-32E. It operates in a series of stages, each stage refining the output of the previous stage. This algorithm is in the second stage. It is the primary obstacle detection method, with the other methods making only small improvements.

The leaked code uses a column-major matrix of points and it explicitly handles NaNs (the no-return points). We've rewritten it to use a much more cache-efficient row-major matrix layout and a conditional that will ignore the NaN points without explicit testing.

This is an amazingly effective method of obstacle detection, considering its simplicity.

Re: A Short Introduction to Automotive Lidar Technology

#15
post #13
post #3

Fantastic tech that Musk hates

So there's a video of him addressing this - he doesn't hate the tech. He mentions that it's wildly expensive for cars. But, they use it heavily for SpaceX

The issue isn't that it's wildly expensive for cars. But rather for Tesla.

Because the company has promised that existing Tesla owners would be able to use FSD.

Having to retrofit them to add LiDAR sensors would be cost-prohibitive.

Re: A Short Introduction to Automotive Lidar Technology

#16
post #13

Earlier quoted context omitted.

So there's a video of him addressing this - he doesn't hate the tech. He mentions that it's wildly expensive for cars. But, they use it heavily for SpaceX

The issue isn't that it's wildly expensive for cars. But rather for Tesla. Because the company has promised that existing Tesla owners would be able to use FSD. Having to retrofit them to add LiDAR sensors would be cost-prohibitive.

Also he wants to reuse the foundational machine vision tech in Optimus bot, which probably won't have lidar.

Re: A Short Introduction to Automotive Lidar Technology

#17

Earlier quoted context omitted.

The issue isn't that it's wildly expensive for cars. But rather for Tesla. Because the company has promised that existing Tesla owners would be able to use FSD. Having to retrofit them to add LiDAR sensors would be cost-prohibitive.

Also he wants to reuse the foundational machine vision tech in Optimus bot, which probably won't have lidar.

Based on presentations we've seen what sets Tesla apart are its datasets not the core technology.

And those don't translate across to the Optimus bot.

Re: A Short Introduction to Automotive Lidar Technology

#18
post #4
post #3

Fantastic tech that Musk hates

It‘s not just Musk. Most automobile manufacturers have maintained that they need to find a way to do it with cheap and pretty sensors.

> have maintained that they need to find a way to do it with cheap

If the goal is to make roads safer. Aiming for cheap is good, it means aiming for more people who can afford that safer car. If it's not safer than humans, it should not be on the road in the first place.

Re: A Short Introduction to Automotive Lidar Technology

#19
post #10
post #8

That's a reasonable basic overview. I'm surprised that rotating scanners are still used. It's been twenty years since Velodyne built their first one. They work OK, but cost too much. I was expecting flash LIDAR or MEMS mirrors to take over. Continental, the auto parts company, bought the leading flash LIDAR company over a decade ago, but the volume market a big parts company needs never appeared. Waymo is still using…

> They work OK, but cost too much. Costs have dropped dramatically in the past 20 years and continue to do so. > There needs to be a cheap, flush-mounted replacement for those things. Why? Corners are the optimal mounting position for maximum visibility. It allows the car to -in-effect- see around corners in ways no centrally mounted sensor can. > Waymo needs to solve that problem before they do New York. What? Becau…

Have you ever seen the corners of a car that has been parked in a big East-coast city? They will sustain damage during the course of normal operation and storage, and many people will not stop and leave their insurance information, especially if the damage is perceived as minor and happens while the car is parked and the owner not present. Currently, the corners of a car are relatively non-critical to its function and usually not too expensive to repair. If both of those change, we'll see more expensive damage that is more challenging to repair as well as less likely to be handled by the responsible party.

Also, having the sensors stick out from the corners makes the car's collision box and turning radius bigger. That doesn't help in any tight situation, but I imagine that's not that different between e.g. SF and New York. What is different is the sheer volume of cars and pedestrian activity.

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