4 ms·

Because lidar is expensive, error-prone, and can't be created without flaws. So if you make a car LIdar will fail way before camera. The only problem is if came

Because lidar is expensive, error-prone, and can't be created without flaws. So if you make a car LIdar will fail way before camera. The only problem is if camera only can work

sangnoir 8y ago
Why not both? Infact, Waymo has Lidar, radar and cameras (Tesla have just the last 2 and are working overtime to demonize the first). More data (and more redundancy) is better - assuming you have the computing power to process all the sensor input. As far as I can tell, the rubbishing of Lidar is FUD.
- DeonPenny 8y ago
  Because if you're using lidar for depth and you try to mass produce the there a high chance the lidar will be broken and because it accurate people will assume it more correctly. Eyes and camera may sometime make mistake with distance but usually it will be software not hardware. Lidar opens the issue for both. So it's easier to use the camera and just try to make a camera as good as lidar.
cr0sh 8y ago
All sensors and the systems they operate with have flaws. There is no way around this - it's just the real world. Even cameras will have flaws, or they can develop them over time (lens degradation, image sensor dropping pixels or gaining stuck pixels, etc). 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.
- grey-area 8y ago
  Cost is also a significant consideration on mass market cars.

Because lidar is expensive, error-prone, and can't be created without flaws. So if you make a car LIdar will fail way before camera. The only problem is if camera only can work

sangnoir 8y ago

Why not both? Infact, Waymo has Lidar, radar and cameras (Tesla have just the last 2 and are working overtime to demonize the first). More data (and more redundancy) is better - assuming you have the computing power to process all the sensor input. As far as I can tell, the rubbishing of Lidar is FUD.

DeonPenny 8y ago
Because if you're using lidar for depth and you try to mass produce the there a high chance the lidar will be broken and because it accurate people will assume it more correctly. Eyes and camera may sometime make mistake with distance but usually it will be software not hardware. Lidar opens the issue for both. So it's easier to use the camera and just try to make a camera as good as lidar.

cr0sh 8y ago

All sensors and the systems they operate with have flaws. There is no way around this - it's just the real world. Even cameras will have flaws, or they can develop them over time (lens degradation, image sensor dropping pixels or gaining stuck pixels, etc). 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.

grey-area 8y ago
Cost is also a significant consideration on mass market cars.