I believe they said that LIDAR was so low resolution and was giving so many false readings that they had to give it up when using it in the real world (non pre-mapped cities like some other companies).
Yes, they have been repeating this argument but intuitively it doesn't doesn't make sense to me. How is it more difficult than stiching a dozen cameras together? Even a single point in the lidar map can provide distance information to giant median columns Tesla cars keep missing. Any computer-vision experts can weigh in on this? Isn't Waymo doing this already?
Another argument is to not fuse the data. Just keep it as a backup decision maker akin to how Aviation systems are designed. If both systems agree, then you have additional reliability. Would love to hear from someone who's worked on these kinds of FSD systems.
>If both systems agree, then you have additional reliability.
Andrej covered this in a previous talk. If both systems agree, then nothing would be different if you did not have the 2nd system. If the systems do not agree then you ultimately still have to pick one in most scenarios.
IE if you are travelling down the highway at 80mph with a car close behind and your lidar+radar system says there's an immediate obstacle but your vision system says it's an overpass, do you emergency brake?
I see, I was thinking about instances where it crashes into pillars which would be pretty obvious case for disgareement between vision and LIDAR. It would alert the driver to take control instead to crashing into it. Tesla autopilot has some scary corner cases where LIDAR can be a backup system for human intervention. But, for FSD level 5 - it's a different story.
Another argument is to not fuse the data. Just keep it as a backup decision maker akin to how Aviation systems are designed. If both systems agree, then you have additional reliability. Would love to hear from someone who's worked on these kinds of FSD systems.