We do a tremendous amount of testing to ensure real-world reliability, and our customers' results bear that out. Full functional safety certification is slated for end of this year, which means it's already well underway.
We make a point of this because legacy spinning lidar is unreliable. But it's unreliable because of the analog design, not because spinning is inherently unreliable.
This is the spec for a cold start. If you give it a warm start, you can operate it much lower than -20C! For instance, it's being used in underground mines in Scandinavia without issue.
This has a single moving part - a brushless motor that turns the turntable. It's rated for over 100,000 continuous hours of operation, and passes automotive shock and vibration standards.
There's a good explanation in the post about what we mean by digital lidar, but the tl;dr version is we use silicon CMOS chips for lasers and detectors vs analog components like side emitting lasers and APDs used by legacy lidar providers.
Solid state is a bit of a buzzword, and most "solid state" lidar sensors actually have small, delicate moving parts inside. Solid state sensors are aimed primarily at consumer vehicles, which are still many years away.
The benefit is (at least in theory) easier integration into the vehicle fascia and (again, in theory) higher reliability vs legacy spinning lidar, which are quite unreliable in the real world.
Ouster's digital lidar sensors are much more reliable than the legacy analog spinning lidar sensors, and much more compact - and therefore easier to integrate.
While this is a ~80% discount on other 128 beam sensors, it's unfortunately still out of reach for the hacker community. We absolutely plan to get prices down to an affordable level for individuals in well under 5 years!
Also, Ouster runs a sponsorship program that gives deeply discounted or free sensors to cool projects. If you have a cool idea, shoot me an email: derek.frome at ouster dot io
"But if Tesla ultimately succeeds, it won't be because it's easier to achieve full autonomy without lidar than with it. It will simply be because Tesla began large-scale data collection from cameras long before other carmakers.
In short, the fact that Tesla backed itself into a corner by promising customers full autonomy without lidar doesn't prove that other companies won't find lidar helpful to their own self-driving efforts."
A great summary. The only thing it misses is that lidar is getting more and more like a depth camera. SPADs can sense ambient light and create 2D images that are perfectly correlated to 3D images, making it possible to apply 2D algorithms to 3D data [1].
Tim is one of the best informed journalists on lidar - and this is a pretty solid summary of where the leading companies are (although Luminar continues to be incredibly misleading).
Ouster | San Francisco,CA USA | Full-time | On-site
Role: Embedded Linux Engineer, C++ generalist, DevOps Engineer (among others - ouster.io/careers)
Product: Publicly we design and manufacture high performance LIDAR sensors that outperform the products from velodyne at much lower cost. The system we've developed has all of the core aspects of an AV - real-time sensor fusion, localization/state estimation, HD map generation, and a realtime perception stack for semantic scene segmentation, object tracking classification and decision making, but many of these modules are in their early stages. We have developed a crowdsourced 3D mapping product that we've been deploying on customer vehicles with the goal of 3D mapping the earth. Product is already shipping to fleets, ride share, and car companies. 65 person company in The Mission, San Francisco.
Yeah - we're actually exploring how to address the industrial market more effectively right now. There's a lot of interest in moving from 2D to 3D lidar.
Part of that is probably just the resolution you're seeing on the point cloud (i.e. if it were up on a 4k OLED you'd see it a lot better than you do on that screenshot) and part of it is definitely that lidar as a broad category has a comparatively harder time with this type of surface than other surfaces. That's why it's super important when comparing lidar units to see what reflectivity they're quoting. 80% vs 10% reflectivity typically reduces range significantly.
PS if you want to get in touch directly, my email is derek.frome at ouster dot io
Costs are definitely coming down. The OS-1 sensor is 1/6 the price of Velodyne's 64 channel sensor. Ouster has been pretty explicit about our intent to keep driving down prices, and we have significant structural advantages covered in the article that will allow us to do so in the coming months and years.
You'd be amazed. I was an account manager at Medallia (Qualtrics competitor, also backed by Sequoia) and the response rates on 20-50 question surveys was typically in the double digits. When you have hundreds of thousands of customers in a month, you can generate super rich data through this process.
However, the industry as a whole has been coping with something they call "survey fatigue" which is reflected in a lot of the comments here. There has been a general backslide in survey response rates, though as of a few years ago, it had mostly stabilized around a new normal that was still plenty good for generating excellent data sets to understand the customer experience.
Worth checking out the Ars Technica article published today which has an independent point of view on the same topic. But FWIW this was written by our engineering team, not marketing.
This has been my experience. For instance, there's a ~40 mile loop in the Sierras that I've done as a 3 day backpacking trip and as a one-day run.
Carrying more means I can bring my nice camera and take photos anywhere I want to stop. But going light and fast means I get to experience the place unburdened, with just food and water on my back.
It's impossible to say one is better or worse than the other. Although I can tell you which one hurt more.