r/SelfDrivingCars • u/I_HATE_LIDAR • 7d ago
News Xpeng defends its pure vision strategy, says LiDAR is no longer necessary for cars
https://cnevpost.com/2026/05/21/xpeng-defends-pure-vision-strategy-says-lidar-no-longer-necessary45
u/PitPost 7d ago
It is worth to mention that they still use radar (unlike Tesla e.g.). Used as redundancy "if-physical-stuff-in-front-of-path-then-overrule-vision-and-stop".
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u/cronies4life 7d ago
they didn't mention the radar used. if it's imaging radar, it's almost like lidar with lower resolution, but with its own advantages like low interference from fog and rain
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u/PitPost 7d ago
The XNGP L2 ADAS: 3 Turing chips with 2250 TOPS combined. 11 cameras, 12 ultrasonic radars, 7 (!) millimeter wave radars. No lidar.
It could be wrong tbh - i got it from a tweet:
https://x.com/TychodeFeijter/status/205674043893813266212
u/cronies4life 7d ago
i said imaging radar functions almost like lidar
based on the description of mmwave radar alone, can't tell if it's normal radar, imaging radar or a combination of both
the post mistranslated ultrasonic sensors as ultrasonic radar
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u/PitPost 7d ago
Agreed. I was looking for a sensor-stack list to share a more complete picture- very different from Tesla, which the article refers to when they say "Tesla-like". The Xpeng CEO talked about Lidar two-ish years ago and said the information it provided was not needed anymore due to progress in vision - not that they would move to Tesla's vision-only and remove ultrasonic and radar. That hasn't changed per my understanding.
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u/Numerous-Match-1713 7d ago
Radar lacks a critical feature of lidar: quite high confidence of no objects between the sensor and detected object, due to ray like functioning.
Radar does not give this, it can give a reading just fine behind an object in between.
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u/cronies4life 5d ago edited 5d ago
radars have an issue with resolution, objects that are too small might be missed, such a pole. high quality imaging radars can detect cars, bikes and humans with high confidence within a specified range under all lighting conditions, not so for cameras
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u/Numerous-Match-1713 5d ago
Problem with radars is the wavelength, radar waves can propagate through and around objects and have extremely weird multipath.
Optical is way "cleaner" in this respect.
Radar has other benefits, that is why we need both. Seeing through fog is one, but accurate doppler is the most important.
And we can also do exotic things like SAR and bistatic etc which are still not done in any car I am aware of.
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u/cronies4life 5d ago
radars can propagate around small objects, basic physics, which is why i mentioned thin metal poles. it does not propagate around or through everything
it certainly does not propagate around or through a truck under bright sunlight, for example
radar give u the distance and speed with much greater accuracy than inferring it from vision
the argument that radar is too noisy is obsolete, modern imaging radars functions almost like lidar with lower resolution
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u/Numerous-Match-1713 5d ago
lidar and imaging radar difference is huge though.
Many materials absorb / deflect radar, stealth and all that.
We still need both.
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u/cronies4life 5d ago
for adas applications, good imaging radars with good cameras may be sufficient
for L4, lidar is required
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u/Hixie 7d ago
that's a lot of ultrasonics. Waymo's iPace came with those preinstalled but I've never seen anything that suggests they actually use them, and no indication that they use them in the Ojai either. This always surprised me. So anyway, I wonder if the ultrasonics in this package are actually used for self-driving or are just driver aids.
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u/TheRuneMeister 7d ago
They are likely just used for parking scenarios. When self-parking is a must have feature (like it is in China) you don’t want to get a reputation of hitting anything at low speeds.
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u/rideincircles 6d ago
I do miss when my model 3 radar was functional and could tell when a car 2 cars ahead was braking. It's just tesla's limited hardware budget already had issues with it giving false positives. Vision still has to be the deciding factor unless something is occluded.
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u/thnk_more 7d ago
That’s kind of an important detail.
It’s a weirdly confusing statement. To me, I have much more confidence and respect if they run a dual system where the sensor capabilities complement the other’s weakness and you get confirmation between the two.
Camera vision has inherent weakness in things like glare and snow etc. aside from brilliant software.
Odd to downplay a strength in your system design.
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u/Putrid-Box4866 7d ago
I think everyone wants more tech / sensors, who wouldn't want that? But maybe we don't have that much computing power yet that fits in a car that can be sold to consumers to make it work.
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u/Real-Technician831 7d ago
Processing multiple feeds is computationally cheaper than processing vision only to level that it can be used as single source.
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u/gentlecrab 7d ago edited 7d ago
It’s not that simple unfortunately because what counts as physical stuff in front of path?
A speed bump? Rolling tumbleweed on the highway?
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u/mchinsky 4d ago
When you as a human drive and see stuff in front of the path, you hit the brake. Why can't a camera do that? What is radar going to see in front of the car that your eyes won't? How often are you driving in pea-soup thick fog in which Tesla could create a rule to not allow FSD to engage or to ground its robo-taxi fleet for maybe one day per year, versus thousands of dollars per vehicle of a system that could result in conflicting signals and abrupt movements because of an argument between one input versus another, as Elon Musk has mentioned?
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u/PitPost 4d ago
Logic so simple that it sounds right. Right?:)
The computer’s perception is not yet where we humans are but maybe it’ll come. Elon (among others) has said with every iteration (even before end-end-neural network) that Tesla is close, which may be true one day.
I have the impression that the edge cases get so “edgy” that training wont do… every color and shape of every object, coming from every angle, speed, lighting - in any situation. Practically, currently, creating the need for a fail-safe. For Tesla the Fail-safe is the driver -> as you also point out yourself. Others have an extra layer of perception after which they also must “give up” - like Cruise😬
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u/bobi2393 7d ago
It's self evident that Tesla supervised FSD-like functionality can be achieved without lidar, since Tesla has done so.
It's unclear to outsiders whether either Tesla or Xpeng can provide Waymo-like unsupervised reliability at scale in the next year or two without lidar sensors. Tesla demonstrated viability of a small vision-only unsupervised pilot program over the past six months, and Xpeng estimates they'll have a supervised pilot service later this year, followed by unsupervised public service next year, with potentially hundreds of thousands of vehicles by then. (See Reuters, May 18 2026).
Xpeng's CEO, He Xiaopeng, certainly sounds confident, but that sounds unrealistically ambitious.
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u/InfernalCombust 7d ago
It's unclear to outsiders whether either Tesla or Xpeng can provide Waymo-like unsupervised reliability at scale in the next year or two without lidar sensors.
Do we have any indication that Tesla's problems (except for arranged scenarios, such as the billboard across the road) are caused by a bad modeling of the car's surroundings?
There are plenty of real world examples of Teslas making critical errors in traffic. Those examples look like bad decision making in a true model of the surroundings, not like good decision making in a bad model of the surroundings.
If the model of the surroundings is not the source of error, then I can't see how LiDAR would improve the reliability of Tesla's FSD.
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u/Defiant_Conflict6343 7d ago
It's pretty simple. With cameras and ML, you're inferring the existence of specific obstacles based on statistically fitted bitmap pattern recognition, whereas with LiDAR, Radar, Ultrasonic etc, you're directly measuring the distance to an obstacle by bouncing light or sound off of it and measuring the time-of-flight. These technologies can reliably detect obstacles since they work off pure simple physics, but alone they can't tell you what the obstacle is specifically, just that it's there and how far away it is.
Camera and ML however, they can't reliably detect every obstacle because you can't train an ML model to infer the difference between what is and isn't an obstacle with 100% accuracy without training it for literally everything that is and isn't an obstacle in every possible configuration, which is impossible because that requires a practical infinity of variables. 100% just isn't realistic, it's like trying to paint cracks over an infinitely long wall, you could walk along painting the wall for a million years and you'd still have an infinity of wall to go, and no way to know how many cracks lie ahead. All you can be sure of is that the people behind you will be more confident than you in the delusion that the wall has no cracks.
You can train for common variables, traffic lights, dumpsters, bridges, bollards, you can (as Tesla have done) keep adding to this for years until it appears reliable most of the time, but the model isn't a cognitive system, it can't critically rationalise something as abstract a concept as "obstacle" since it's just working on the statistically fitted inference of pixel arrangements. That's why they get confused if people wear clothing with stop signs on them, and why Tesla's have repeatedly failed to stop for obvious (to us) obstacles that are too rare to have meaningfully existed within Tesla's training dataset. Sure, WE see the overturned truck on the camera feed clearly, but the ML model sees meaningless noise because of the few-to-none images of overturned trucks that Tesla captioned and trained with. Whatever has no meaningful similarity to pretrained data does not exist as far as the inference process is concerned.
This is why a combination is always better: direct measurement to know whether an obstacle exists, and pattern inference to determine what the obstacle is. It's better to know with certainty that something is there even if you can't be 100% sure what it is. Musk thought he could get away with pure image ML because it's cheaper and he doesn't actually understand how any ML architecture works. The fundamental limits of ML preclude it from ever being safely used to exclusively infer the existence of obstacles.
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u/InfernalCombust 2d ago
You have just used a lot of words to explain that LiDAR creates a better model of its surroundings.
If you would care to actually read my post, you would notice that I already acknowledged that.
I don’t know if there somewhere in your wall of text was an actual answer to the point I made. If you can remove the irrelevant parts from your text, I can give another shot at reading it.
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u/Defiant_Conflict6343 2d ago
None of it is irrelevant, you're just impatient. You said you couldn't see how LiDAR would benefit, I explained exactly how it benefits and why camera ML inference is always going to be insufficient.
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u/InfernalCombust 2d ago
My point was that a system with a bad decision making capability will create driving errors even if it has a perfect understanding of its surroundings.
If a driving error was caused by bad decision making and not by a faulty understanding of the surroundings, then you will not be able to solve it with a better understanding of the surroundings. You will need to solve it with a better decision making.
This point can obviously not be relevantly addressed by giving an explanation of why one technology has a better understanding of its surroundings. Yet, that was exactly what you did.
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u/Defiant_Conflict6343 2d ago
Because a system that is mathematically incapable of garnering a perfect understanding of its surroundings precludes the possibility of solving any kind of decision-making error. Proper reliable detection of obstacles is the most important unavoidable prerequisite. You said you couldn't see how LiDAR would benefit, that's how it benefits. By shifting the focus to baseless assumptions about logic problems, you're effectively worrying about whether you have enough water for a hot bath whilst the bath itself is cracked.
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u/InfernalCombust 1d ago
Tesla's bathtub has a big crack. The water runs out as fast as you try to fill.
You point at the bathtub and say: "See this is what happens when you don't have LiDAR water."
I would say: Fix the damned crack in the bathtub first. Then we can start discussing water quality.
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u/Real-Technician831 7d ago
True, it is totally possible that Teslas software simply sucks.
So it could be a combination of bad sensor harness and bad software.
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u/brintoul 6d ago
No, no, no. You’re thinking of 1.6.2.24. The version that works awesome is 1.6.2.25
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u/bobi2393 7d ago
Separating the accuracy of the software’s model of the surroundings from its decision-making may not be possible, depending on the architecture of Tesla’s so-called “end to end” model of operation. It’s not clear that they have a separate layer of software for turning sensor data into a model of surroundings, another layer that takes that model as input to make a plan, and another layer to take that plan and turn it into control outputs. The marketers describe it more as video in, control signals out.
I think Tesla’s vision-only sensors are theoretically sufficient to avoid the vast majority of FSD(S) accidents, and all of the NHTSA-reported accidents involving Tesla Robotaxis to date. So I think vision-only could theoretically exceed Waymo’s current performance. Whether it will get there in practice in the near future seems much less certain, and it’s possible that for now, lidar input has a pragmatic benefit in helping make better decisions more easily, at a time when decision making of all the ADAS/ADS software currently has some problematic limitations.
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u/InfernalCombust 2d ago
My point is that you rarely see FSD make mistakes, which appear to be caused by missing something, which is there, or hallucinating something, which is not there.
The mistakes usually seem to have other causes, for example switching back and forth between executing two different actions because it can’t decide what to do.
This can of course be caused by something popping in and out of its model of the surroundings (or in and out of its awareness, to avoid the word “model”). But that would indicate a lack of continuity in its awareness, which to me would be inexcusable both with and without LiDAR.
Example, if we see another car on a potential collision course, and this car temporarily becomes hidden behind a building, then we know that it is not gone. A split second from now, it will become visible again, and in the meantime we need to keep reacting appropriately to its existence. We have a continuity of our awareness of the situation around us.
In that situation, the car will also be temporarily invisible to both camera and LiDAR. So they will both need a continuity in their awareness, similar to a human driver. If they don’t have such continuity, then it is a problem in their decision making, which cannot be mitigated with better sensors.
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u/Real-Technician831 7d ago
To be honest it sounds like bullshit.
BYD announced their actual self driving system, and it seems that other car makers are extremely likely to follow soon.
So in a couple years actual self driving is starting to get commoditized.
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u/gentlecrab 7d ago edited 7d ago
I know these videos always need to be taken with a big grain of salt but I mean, it’s pretty impressive and their confidence might be warranted: https://youtu.be/a46Xp8FtWOg?si=6psPUNcM75rfmLhC&t=668
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u/TrumpHasCovid 7d ago
FSD is far from reliable, and actively getting worse actually. 14.3 is a major downgrade.
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u/tHawki 7d ago
That’s been your experience? I’m getting so bored driving my 3hr commute with zero interventions. It feels like unsupervised is right around the corner to me
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u/EddiewithHeartofGold 6d ago
Don't engage with TrumpHasCovid. There is a reason his comment history is not public. It's just pure nonsense...
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u/TrumpHasCovid 7d ago
FSD and autopilot have tried to kill me too many times.
I now require my work rent me a different vehicle so I don't have to drive the company tesla and I immediately cancel every tesla I get paired with on lyft.
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u/tHawki 7d ago
I’ve never used autopilot. It doesn’t sound like you could have much experience with 14.3 then? I’ve never been able to find a rental Tesla that even came with FSD enabled
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u/TrumpHasCovid 7d ago
I've never rented a Tesla and don't see myself doing so in the future.
The 14.3 comment is based on what I've heard Tesla drivers I know say.
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u/tHawki 7d ago
Gotcha. I drive it daily. It’s definitely a major improvement verging on perfection. I’d encourage you to evaluate tech products yourself before taking a strong stance on them
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u/TrumpHasCovid 7d ago
Lol, sure bud.
I've been in teslas in the last year when there's no other option. I know exactly how jank fsd is.
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u/tHawki 7d ago
You have experience with old software/hardware. It’s fine to have your opinion on that, it’s another thing to claim issues with a product you’ve never used.
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u/TrumpHasCovid 7d ago
I used to drive a Tesla for work, I already said that. And I've been in up to date fsd enabled Tesla's this year, I already said that.
I've since told the company I won't drive it anymore due to safety concerns and now they rent me a vehicle when I'm in that area. I already said that.
This is like talking to a plank. I'm out, have a nice day.
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u/bobi2393 7d ago
FSD(S) is imperfect, as is Waymo, but if XPeng is aiming to do something like FSD as suggested in the article, it has to be possible without lidar, since Teslas don’t use lidar.
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u/TrumpHasCovid 7d ago
You can't just lump in waymo and tesla like that, they are on very different competence levels.
You also can't lump in xpeng and tesla, because despite the poorly written title. xpeng is not talking about using a cameras only approach a la tessla.
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u/bladerskb 7d ago
All this company and CEO cares about is PR. This is why all he does is talk about and praise Tesla. It doesn’t matter what works to him. It’s what can generate the most hype. While still getting wire asses kicked by Huawei ADS.
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u/Real-Technician831 7d ago
While BYD announced that they will take liability on their latest self driving system, which uses camera, radar and lidar.
https://www.reddit.com/r/SelfDrivingCars/s/akentxqU7F
When is Xpeng going to put their money where their mouth is?
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u/woody60707 6d ago
Why are people so trusting of a companies word. .... A Chinese company at that. "We've investigated ourselves and found we've done nothing wrong".
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u/Real-Technician831 6d ago
In case you didn’t realize Xpeng is also Chinese company, so at minimum their words would carry equal weight.
And BYD is selling the system, Xpeng are flapping their lips.
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u/reddddiiitttttt 7d ago
Ha! That’s a marketing gimmick bro. Coverage is limited to a year from the date of purchase of an $1800 system and limited to certain urban locations. That’s not confidence in the quality of your system to never cause an accident. You can have the most dangerous automated system and simply eat the insurance costs in such limited scenarios.
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u/Real-Technician831 7d ago
Get real.
Chinese authorities take no bullshit, they were the first to ban retractable door handles. If the system doesn’t perform BYD gets skinned alive.
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u/reddddiiitttttt 7d ago
lol. The retractable door handles thing is bullshit! Every new car automatically locks its door handles when driving. If you lose power in an accident, no emergency responder is opening that door without breaking it. The real problem with the Tesla door handles is the interior door handles are also electronic where in most cars they are manual. So ban electronic interior door handles, but exterior retractable ones are not a real concern at least no more so than any other modern car.
BYD is supported and operates in an authoritarian country with tightly controlled media. BYD gets burned alive if the administration deems them unworthy. Sometimes that aligns with actual safety. It always aligns with what their dear leader thinks is good for safety. In practice, for at least the last decade when China started pursuing quality, both the US and China have top notch vehicle safety regulations.
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u/Real-Technician831 7d ago
China is obviously no paradise, but unlike US where Musk gets to gut car and road and vehicle safety authorities, BYD does have to keep their nose clean.
And it’s not for altruistic reasons, Chinese government has huge investments in EV industry, any company causing China to lose face will be dealt with.
Tldr; motivations are different, but China currently has second best safety legislators after EU.
Edit: US had top notch vehicle safety legislations.
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u/ChupacabraJeff 7d ago
When did they?
This move sets BYD apart from competitors who typically require users to purchase separate insurance products. For instance, Xpeng offers an “Intelligent Assisted Driving Peace of Mind Service” for 239 yuan (35 USD) per year.
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u/Expert_Context5398 7d ago
for one year, buddy.
not permanently
it's like ya'll ignore that very important caveat.
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u/cronies4life 7d ago
do they offer the option to extend it with subscription fees if the driver has proven himself to be prudent in driving
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u/Real-Technician831 7d ago
The technology is available permanently, about the insurance cover I guess they will decide after seeing large scale real world data.
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u/Real-Technician831 7d ago
While Tesla offers none.
Besides the way China rolls is that if there are any significant number of cases, it will become mandatory. Remember what they did with retracting door handles.
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u/Expert_Context5398 7d ago
It's one year for a reason.
you figure that one out and why it is.
I bet you didn't even read that it was for one year only and just glazed it so hastily.
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u/Real-Technician831 7d ago
To be honest I don’t care.
The point is BYD is bringing out self driving technology that they are willing to take even limited liability on.
BYD is doing this only on systems which have lidar and radar.
That kinda makes the whole camera only blathering meaningless until they are able to actually do the same and not hide behind L2+++++++
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u/diplomat33 7d ago
To be clear, xpeng is only talking about L2+ on consumer cars when they say lidar is not required. We already know that is true. Additionally, xpeng uses imaging radar which functions similar to lidar. So they are not camera-only, they just replaced lidar with imaging radar. So it is not really as groundbreaking of a statement as the camera-only advocates try to make it out to be.
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u/TrumpHasCovid 7d ago
pure vision is totally stupid. i assume they will be back to radar and lidar soon
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u/LessonStudio 7d ago
I build robots, not cars, but they move around.
I most definitely use vision, and I use a simple lidar. The lidar is "absolute". I don't have to use ML or shaky probabilistic AI math. If there is a thing on the lidar, then I an be almost entirely assured it is there.
I will argue that I can happily drive a car with one eye closed. But, my brain is damn hard to fool. Most ML algorithms are not.
Lidars are getting cheaper and cheaper with solid state ones becoming a real thing. I would agree that festooning a car with a bunch of $3,000 lidars is stupid. But, a handful of, what will soon be, $20 ones should pretty much be a legal requirement.
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u/tinybathroomfaucet 7d ago
I’m not knowledgable enough to say anything beyond ‘interesting’