4 ms·

So much for the folks who think Tesla is on a fool’s errand when they’re using cameras instead of LIDAR.

by leobg 5y ago

kajecounterhack 5y ago
Companies like Waymo and Cruise use this kind of technology too. Unfortunately there are tons of corner cases of weird things you haven't seen before -- for example, some special vehicles self-occlude and you never get enough coverage to observe them correctly until you're too close. In general, radars and lidars used in _conjunction_ with cameras can handle occluded objects much better. Also, to measure the performance / evaluate observations generated from this tech, you would want to compare it to a pretty sizable 3D ground truth set which Tesla does not currently have. There are pretty big advantages to starting with a maximal set of sensors even if (eventually) breakthroughs turn them into unnecessary crutches.
- leobg 5y ago
  That was very insightful. Do you work in that space? It is comments like yours that make HN a special place.
- quantumduck 5y ago
  I agree that there are pretty big advantages to start with maximal set of sensors, but that is true only when you are a company with the sole goal of trying to make autonomy stack with shit ton of money and a product that you can modify because you own it. That's not true in the case of Tesla. They started as a EV company that offered autonomy later and since they were selling the product, they had to decide a minimal set of sensors that would, in theory, still work to keep the product cost reasonable. Tesla does have a sizeable 3D ground truth; they collected tons of data mounting LiDAR on their test vehicles.
  - kajecounterhack 5y ago
    > Tesla does have a sizeable 3D ground truth; they collected tons of data mounting LiDAR on their test vehicles. "Sizable" for evaluating safety has to be big enough to give small confidence intervals on your error -- and with self-driving, you need to cover a robust set of rare scenarios upsampled from general driving as well. I really doubt Tesla has what they need to convince themselves of higher levels of safety.
ceejayoz 5y ago
The failure mode (for example: decapitation; https://www.latimes.com/business/la-fi-tesla-florida-accident-20190302-story.html https://www.latimes.com/business/la-fi-tesla-florida-acciden...) is pretty significant when used in a Tesla. Less so in this tech demo.
upbeat_general 5y ago
The use-case of 3D reconstruction vs real-time inference can be very different (but certainly related). Monocular 3D reconstruction can require many frames at many angles (or possibly just a few frames at sparse angles). The inference case with a self-driving vehicle may allow for this in some scenes, but certainly not all. Trying to infer the relative motion of say two moving vehicles and getting enough frames for monocular reconstruction may take longer than is required for an emergency break, not to mention the robustness issues with those pose estimations without additional sensors. Solving any one of these issues can be done but I think it’s pretty clear we’re a bit away from solving all of them.

So much for the folks who think Tesla is on a fool’s errand when they’re using cameras instead of LIDAR.

by leobg 5y ago

So much for the folks who think Tesla is on a fool’s errand when they’re using cameras instead of LIDAR.

Companies like Waymo and Cruise use this kind of technology too. Unfortunately there are tons of corner cases of weird things you haven't seen before -- for example, some special vehicles self-occlude and you never get enough coverage to observe them correctly until you're too close. In general, radars and lidars used in _conjunction_ with cameras can handle occluded objects much better. Also, to measure the performance / evaluate observations generated from this tech, you would want to compare it to a pretty sizable 3D ground truth set which Tesla does not currently have. There are pretty big advantages to starting with a maximal set of sensors even if (eventually) breakthroughs turn them into unnecessary crutches.

leobg 5y ago
That was very insightful. Do you work in that space? It is comments like yours that make HN a special place.
quantumduck 5y ago
I agree that there are pretty big advantages to start with maximal set of sensors, but that is true only when you are a company with the sole goal of trying to make autonomy stack with shit ton of money and a product that you can modify because you own it. That's not true in the case of Tesla. They started as a EV company that offered autonomy later and since they were selling the product, they had to decide a minimal set of sensors that would, in theory, still work to keep the product cost reasonable. Tesla does have a sizeable 3D ground truth; they collected tons of data mounting LiDAR on their test vehicles.
- kajecounterhack 5y ago
  > Tesla does have a sizeable 3D ground truth; they collected tons of data mounting LiDAR on their test vehicles. "Sizable" for evaluating safety has to be big enough to give small confidence intervals on your error -- and with self-driving, you need to cover a robust set of rare scenarios upsampled from general driving as well. I really doubt Tesla has what they need to convince themselves of higher levels of safety.

ceejayoz 5y ago

The failure mode (for example: decapitation; https://www.latimes.com/business/la-fi-tesla-florida-accident-20190302-story.html https://www.latimes.com/business/la-fi-tesla-florida-acciden...) is pretty significant when used in a Tesla. Less so in this tech demo.

upbeat_general 5y ago

The use-case of 3D reconstruction vs real-time inference can be very different (but certainly related). Monocular 3D reconstruction can require many frames at many angles (or possibly just a few frames at sparse angles). The inference case with a self-driving vehicle may allow for this in some scenes, but certainly not all. Trying to infer the relative motion of say two moving vehicles and getting enough frames for monocular reconstruction may take longer than is required for an emergency break, not to mention the robustness issues with those pose estimations without additional sensors. Solving any one of these issues can be done but I think it’s pretty clear we’re a bit away from solving all of them.