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Again with the LIDAR argument... Humans drive using only eyes (computer vision) and having a sense of location (localization/3D maps). Early autonomous test ve

by xedeon 8y ago

Again with the LIDAR argument... Humans drive using only eyes (computer vision) and having a sense of location (localization/3D maps). Early autonomous test vehicles used LIDARS because camera and compute tech are not at the same level they are today. It's a legacy system and more of a shortcut. In essence, Object recognition > LIDAR judging distances. Yeah it's true that a vision based system is much harder to solve. However if Tesla cracks it, it will pay dividends.

DmenshunlAnlsis 8y ago
Again with the LIDAR argument... Humans drive using only eyes (computer vision) and having a sense of location (localization/3D maps). As has been discussed in some depth here before you commented, computer vision hooked up to some ML doesn’t come close to human eyes controlled by a human brain trained for many years. Early autonomous test vehicles used LIDARS because camera and compute tech are not at the same level they are today. It's a legacy system and more of a shortcut. In essence, Object recognition > LIDAR judging distances. Waymo is the cutting edge if you believe what people here say on thread after thread about them, and the raw stats. I’m sure they’ll be interested to hear your view of their “legacy” tech. Yeah it's true that a vision based system is much harder to solve. However if Tesla cracks it, it will pay dividends. Finally, reality. Yes, if they do something they’re yet to do, and their cars stop ramming stationary objects, then maybe something else will happen. No one is contesting that, there are just doubts given the state of Autopilot vs. leaders in the field, not to mention Tesla’s dodgy PR in general, and in the face of fatal incidents in particular.
gamblor956 8y ago
LIDAR provides more than just distances. With full-360 LIDAR you also get object edges in 3d space, which means you can do object recognition on the LIDAR results. In other words, you get everything that vision systems would offer except color, without having to do any processing to calculate depth, so you can go straight to the object-recognition and navigation processing. LIDAR > vision systems.
- deleted 8y ago
  [deleted]
- vl 8y ago
  Also tells you where the rain is.
mnl 8y ago
Humans have general intelligence, that's why they recognize lane dividers and can tell where a truck ends, we kind of expect such things. Also why inebriated people can drive somehow (of course they shouldn't but I'm making a point). Maybe driving on the roads we have now with computer vision alone needs strong AI, maybe simpler standardized roads and vehicles are needed, who knows. I think that strong statements about this should be backed by evidence, not gut feeling. And I'd like to see that evidence coming from the company that promises their customers their cars have all the hardware they need.
baybal2 8y ago
Plain radars are still vastly superior to all and every vision system on the market, and don't require you to carry around a supercomputer. Even if they "crack" it, they will just be spending much more money to get the same benefits as a $100 mm wave system. In the future, vision systems will only be seen as a gimmick of this era. Radars beat both ladars and vision systems at phase, speed, and distance estimation.

by xedeon 8y ago

DmenshunlAnlsis 8y ago

Again with the LIDAR argument... Humans drive using only eyes (computer vision) and having a sense of location (localization/3D maps). As has been discussed in some depth here before you commented, computer vision hooked up to some ML doesn’t come close to human eyes controlled by a human brain trained for many years. Early autonomous test vehicles used LIDARS because camera and compute tech are not at the same level they are today. It's a legacy system and more of a shortcut. In essence, Object recognition > LIDAR judging distances. Waymo is the cutting edge if you believe what people here say on thread after thread about them, and the raw stats. I’m sure they’ll be interested to hear your view of their “legacy” tech. Yeah it's true that a vision based system is much harder to solve. However if Tesla cracks it, it will pay dividends. Finally, reality. Yes, if they do something they’re yet to do, and their cars stop ramming stationary objects, then maybe something else will happen. No one is contesting that, there are just doubts given the state of Autopilot vs. leaders in the field, not to mention Tesla’s dodgy PR in general, and in the face of fatal incidents in particular.

gamblor956 8y ago

LIDAR provides more than just distances. With full-360 LIDAR you also get object edges in 3d space, which means you can do object recognition on the LIDAR results. In other words, you get everything that vision systems would offer except color, without having to do any processing to calculate depth, so you can go straight to the object-recognition and navigation processing. LIDAR > vision systems.

deleted 8y ago
[deleted]
vl 8y ago
Also tells you where the rain is.

mnl 8y ago

Humans have general intelligence, that's why they recognize lane dividers and can tell where a truck ends, we kind of expect such things. Also why inebriated people can drive somehow (of course they shouldn't but I'm making a point). Maybe driving on the roads we have now with computer vision alone needs strong AI, maybe simpler standardized roads and vehicles are needed, who knows. I think that strong statements about this should be backed by evidence, not gut feeling. And I'd like to see that evidence coming from the company that promises their customers their cars have all the hardware they need.

baybal2 8y ago

Plain radars are still vastly superior to all and every vision system on the market, and don't require you to carry around a supercomputer. Even if they "crack" it, they will just be spending much more money to get the same benefits as a $100 mm wave system. In the future, vision systems will only be seen as a gimmick of this era. Radars beat both ladars and vision systems at phase, speed, and distance estimation.