Alas, the price of these devices has to come down at least one order of magnitude. Maybe even two. Still, I am really thankful that other companies (since Tesla has no interest in it) are considering and further developing LIDAR.
Alas, the price of these devices has to come down at least one order of magnitude. Maybe even two. Still, I am really thankful that other companies (since Tesla has no interest in it) are considering and further developing LIDAR.
Lots of things could fix this, less beam divergence, custom signals processing on multiple returns. But out of the box, it’s this statement does not hold true.
For vehicle applications specifically probably worth looking into what they use on autonomous vehicles at mine sites imagine that tech probably useful in agriculture. For example Pilbara here in Australia large autonomous fleets in very dusty conditions.
Just because LIDAR doesn't make sense for the Model 3 today, doesn't mean it should be entirely discounted.
Tesla cars have radar which can see through any weather condition and detect transparent surfaces, invisible to LIDAR.
I'm curious why there is such an apparently long delay?
Like I said I was just speculating about why OP specifically mentioned 10-100ms. the light does indeed travel pretty quickly (although, as anybody in the radar/lidar industry will tell you, not nearly quickly enough!), however the round trip time is just the minimum latency you have to eat to get any information about your target. Once you have light coming back, you need to integrate for some about of time to achieve your desired SNR. That time could be very small, or it could be infinite if there are no photons coming back. Let's randomly say that you're using a RADAR with a Tx bandwidth situated such that the round trip time is 1us, and that your target range is s.t. the beat frequency of the return is 1kHz. Your job is to estimate that frequency, so you have to observe the waveform (by integrating samples for an FFT, typically) for at least one cycle of the RF wavelength. That would require that you wait 1us for the light to fly, and then wait another 1ms for the RF to cycle once. So your measurement latency is ~1ms. Now that's not 100ms, but perhaps you need more than one cycle to give a good estimate of the frequency, and then even more because the target is faint and there aren't many photons coming back. You could possibly arrive at some much higher number, like 10-100ms.
I'm not sure if that was OP's point, but that's all I'm saying ;-)
I think Google's own unit has 8 stored returns.
Simply depends on what wavelength of light you use.
Water-absorbing frequencies are nice because the atmosphere then shields most light, giving you nice SNR from your laser illumination. But better sensors could work around this, using other frequencies that can 'see' through fog.
It's certainly a technological limitation of current systems, but it's not an inherent limitation.
A $100k fully autonomous taxi would print money over its service life (right now they have remote safety drivers on standby).
The question is how quickly they can expand their currently tiny geofenced area.
This is single unit pricing. Volume discounts apply. Still work to do to get this in every honda civic, but it is possible with our technology.