[HN Gopher] New Lidar System Promises 3D Vision for Cameras, Car... ___________________________________________________________________ New Lidar System Promises 3D Vision for Cameras, Cars, and Bots Author : rbanffy Score : 71 points Date : 2022-04-25 16:25 UTC (6 hours ago) (HTM) web link (spectrum.ieee.org) (TXT) w3m dump (spectrum.ieee.org) | rsp1984 wrote: | This is not a "true" LiDAR in the classical sense (where you send | out a laser beam and measure time passed until return). It's | rather an indirect ToF sensor that uses modulated light bursts | that flood the entire scene. | | This approach typically works well for close-range convex | surfaces (hand tracking, bin picking, face ID) but fails pretty | miserably when longer ranges and concave surfaces are involved, | due to quadratic signal dropoff and multipath errors. | | As far as I understand, what the team has achieved is lowering | the power requirements for the modulation part. It means they can | spend the saved power on making the modulated light brighter, | which should give them a bit more range. I haven't seen any other | major improvements though and none of the other issues with iToF | were addressed. | | Not trying to downplay the achievement, just saying it is still | affected by the usual tradeoffs and probably just occupies | another niche in the high dimensional space of 3D cameras, rather | than spanning many of today's niches. | rowanG077 wrote: | I'm curious since you know your stuff. Is structured light a | form of modulated light? | rsp1984 wrote: | Nope. Structured light is projecting a geometric pattern into | the scene and viewing it from from a camera that's offset by | some amount vs. the projector. The original Kinect works this | way. | robotresearcher wrote: | Structured light is modulated in space rather than time. | Accordingly, distance is inferred from offset in space | (pixel, ie. angle) rather than time (phase). | Animats wrote: | _This approach typically works well for close-range convex | surfaces (hand tracking, bin picking, face ID) but fails pretty | miserably when longer ranges and concave surfaces are involved, | due to quadratic signal dropoff and multipath errors._ | | Exactly. This has been used before for short-range sensors, | modulating the outgoing light electrically. Microsoft used it | in the second generation Kinect. Mesa Imaging used it in | 2013.[1] The prototype of that was shown in 2003.[2] I looked | into this in my DARPA Grand Challenge days. | | Since it's a continuous emission system, you need enough | continuous light to overpower other light sources. Filters can | narrow the bandwidth, so you only have to be brighter at a | specific color. This works badly outdoors. Pulsed LIDARs | outshine the sun at a specific color for a nanosecond, and thus | can be used in bright sunlight. Also, they tend not to | interfere with each other, because they're receiving for maybe | 1000ns every 10ms, or 0.01% of the time. A little random timing | jitter on transmit can prevent repeated interference from a | similar unit. | | So, short range use only. For more range, you have to use short | pulses. | | For short range, there's another cheap approach - project a | pattern of random dots and triangulate. That was used in the | first generation Kinect and is used in Apple's TrueDepth phone | camera. | | [1] https://www.robotshop.com/community/blog/show/mesa- | imagings-... | | [2] https://www.researchgate.net/publication/228602757_An_all- | so... | rsp1984 wrote: | Interesting bits about pulsed LiDAR. Is there any camera | available to buy on the market that uses this technology? | titzer wrote: | While this is cool, I think we should seriously take a look at | how insects navigate 3d spaces. They typically have compound | eyes, where each eye-let incredibly simplified (in fact, early- | stage evolution) photoreceptor that has independent connections | in the brain. They have crappy resolution but incredibly good | response time and spatial awareness. And they are _super_ low | power. | peteradio wrote: | But cars don't navigate 3d spaces, it seems like that would | make results not so transferable. How does a fly avoid in-air | collision with another fly? Answer: it doesn't need to. | danbruc wrote: | What happens in busy places when tens or hundreds of vehicles or | robots illuminate the environment? How do several independent | time-of-flight camera systems coexist? Are there existing | solutions from other areas that are already using time-of-flight | camera systems? | xnx wrote: | Not as big a problem as you might think: | https://ideas.4brad.com/tricking-lidars-and-robocars#:~:text... | alimov wrote: | > What happens in busy places when tens or hundreds of vehicles | or robots illuminate the environment? | | I think about this one a lot. While I haven't looked into it I | wonder if this will impact insects and birds somehow | ARandomerDude wrote: | Headline 2035: terrorists cause 200 car pile up with cheap | DRFM-like device. | | https://en.wikipedia.org/wiki/Digital_radio_frequency_memory | rbanffy wrote: | Cars (of 2035) ought to have multiple sensors and should be | able to discard discrepant input - if (stereo) visual, radar, | sonar and lidar disagree, the car should switch to a | "degraded safe" self driving mode and signal it to cars | around it via multiple channels (visual, radio, ultrasound, | etc). | bdamm wrote: | Cars of today already have this problem. If one sensor says | there's a solid object right in front of you that just | popped out, and another sensor says there probably isn't | but is confused, what do you do? Slam on the brakes? | | Teslas today have this "degraded mode" and the reaction is | to sound an alarm and ask the driver to pay attention and | grip the wheel, while slowing. This seems like a reasonable | thing to do. Cars of 2035 that have no wheel better have | perfect sensor integration and false-data elimination. | AlotOfReading wrote: | You can't and won't get perfect sensing. It's simply not | possible. | | A safe vehicle design avoids the situation of having to | decide whether to slam on the brakes constantly by | realizing that's a fundamentally unsafe mode to be | operating in. You should already be slowing/able to | safely brake/pulling over/stopped before that point | excepting rare "everything explodes simultaneously" | situations you can try to engineer away with safety | ratings and MTBF numbers. | rbanffy wrote: | > A safe vehicle design avoids the situation | | And, since you aren't driving a fully automated vehicle, | it driving below speed limits becomes much less annoying | (and, if all cars can coordinate their speeds, prevent | traffic jams altogether). | rbanffy wrote: | If you have two sensors, you have one. You can't resolve | a disagreement of two sensors. Stopping the car is the | only option in this case, but, say, if you have four | sensors and one says there is 100% certainty of a solid | object ahead of you, one says it's 50/50 and two others | say it's a 100% no, then a mild braking action may be all | that's needed, to give the car and its sensors more time | to react and assess. Worst case scenario you still hit | the solid object at an easily survivable speed. You also | signal cars behind you to actuate their brakes | accordingly (and, in turn, inform traffic behind them of | their actions). | samstave wrote: | And it gets way more interesting when every care itself | is a cluster, or node of sensors, and all of these | sensors of the same type can form telemetry fabrics of | all the families of sensor-types across the nodes. | | Each a plane, and then ultimately being able to see the | relationships of patterns of sensor groups. I wonder how | that information will become useful? | rbanffy wrote: | First use could be to model traffic patterns - as | undoubtedly all online mapping apps already do. As the | meshes get denser, the cars can become aware of traffic | patterns around them and make decisions in a coordinated | way, forming "trains" to reduce drag in highways, for | instance. Eventually enough data is gathered that we have | predictive models for traffic jams and accidents and can | act to prevent them. | samstave wrote: | exactly | Tade0 wrote: | > You can't resolve a disagreement of two sensors. | | Two sensors are still useful when all you need to know is | if there's a disagreement. | rbanffy wrote: | True, but the usual action is to hand the decision to the | human, who can look out, figure out which (if any) sensor | is right, and take appropriate action (737 Max feelings). | shadowgovt wrote: | Drivers of today also have this problem in the form of a | lack of standards for vehicle height and headlight power. | [deleted] | UberFly wrote: | The futuristic crime dramas and games where they replay events in | a simulated 3D space is getting closer. Imagine public spaces | constantly scanned and recorded right down to the dropped | cigarette. | nynx wrote: | This is great-hope it pans out and makes it to market quickly. | throwaway4aday wrote: | This will be huge for VR/AR progress. | rbanffy wrote: | Imagine Google Earth and Street View (and their counterparts), | but with almost real time 3D maps. | wlesieutre wrote: | It's not real time, but Apple's map scans are much more 3D. | Like Google Maps you can't make small movement adjustments in | between designated viewpoints, but the animation of moving | from one point to another is pretty slick. | | https://youtu.be/Rd8VltIAZjU?t=36 | rbanffy wrote: | Now, imagine that, using car sensors, you could time travel | and see the same point in space, but at any point in time | (after the introduction of cars that contribute their | sensor data to a consolidated repository of "4D" data. ___________________________________________________________________ (page generated 2022-04-25 23:01 UTC)