This assumes depth information is required for self driving, I think this is where we disagree. Tesla is able to reconstruct its surroundings from visual data only. In biology, most animals don’t have explicit depth information and are still able to navigate in their environments. Requiring LIDAR is a crutch.
I disagree with you, I don’t think visual camera’s alone are up to the task. There was an instance of a Tesla in auto pilot mode driving at night with the driver being drunk. This took place in Texas on the high way, the car’s camera footage was released and it showed the autopilot not identify the police car in the lane with it’s red/blue lights flashing as a stationary obstacle. Instead it didn’t realize there was a car in the way around 1 second before the 55 mph impact, and it turned of autopilot that 1 second before.
Having multiple layers of sensors, some being good at actually sensing a stationary obstacle, plus accurate range finding, plus visual analysis to pick out people and animal, thats the way to go.
Visual range only cameras were just reported to have a harder time recognizing people of color and children.
the car’s camera footage was released and it showed the autopilot not identify the police car in the lane with it’s red/blue lights flashing
If the obstacle was visible in the footage, the incident could have been avoided with visible spectrum cameras alone. Once again, a problem with the data processing, not acquisition.
If we’re talking about the safety of the driver and people around them, why not both types of sensors? LIDAR has things it excels at, and visual spectrum cameras have things they do well too. That way the data processing side has more things to rely on, instead of all the eggs in one basket.
