“Anyone using Lidar is doomed”
Strong words from Musk about sticking with video only.
Later on in the software talk:
“Lidar is really a shortcut which sidesteps the fundamental problems...and gives us a false sense of progress”
Strong words from Musk about sticking with video only.
Later on in the software talk:
“Lidar is really a shortcut which sidesteps the fundamental problems...and gives us a false sense of progress”
Doubt it.
That is point behind what is known as "probabilistic robotics" - the real world has noise, and you need to be able to deal with it. Don't expect perfect sensors, don't expect a perfect environment.
Self-driving vehicles are the application of probabilistic robotic principles to a real-world task - quite possibly one of the most difficult tasks for the field. To be quite honest, it's amazing how well it's worked in such a short period of time.
I think cameras and machine vision approaches will be needed for self-driving vehicles to be fully successful, but I wouldn't say that LIDAR should be counted out. It will probably be necessary - even required - to have all of the sensors currently being used, not just a subset.
One kind of sensor that hasn't been explored much that I think will be needed is some kind of audio input; some kind of wide-range microphone (probably binaural or stereo) to take in environmental audio and use that for driving cues. Some simple examples might be for vehicle horns, or the squeal of tires, or the revving up of an engine indicating someone is speeding up aggressively, or an emergency siren, etc.
There may even be other sensors needed or that could provide other data to fill in certain gaps of environment knowledge to help a self-driving vehicle navigate. I don't think any one or another should be discounted.
Lidar is expensive, and gives surprisingly limited data (just points of depth) and is like a crutch that will only get so far. It will not get you to full autonomy so why not spend the time and money on vision which will (as proven by humans). They also do use radar and ultrasonics (not visual spectrum).
At some point your machine must be good enough via machine learning to give a very good impression of understanding intention in other road users, pedestrians etc. One example they gave was a distracted pedestrian with a phone. Lidar tells you nothing save an obstacle is on the pavement, it won’t tell you they might step out without looking, but machine learning on a massive dataset can.
Once Tesla can actually handle those two extremely basic tasks maybe they can start talking about how vision is better than LIDAR. Until then, it's just more hot air, and that's not even taking into account Tesla's claims of using ML to predict the actions of uncontrolled independent agents in the field of view.