1) We are mostly built on ROS (for better and worse) and are starting to migrate some containers to ROS2. Down the road I see an architecture that has some ROS, some ROS2, and maybe some homemade stuff (or maybe even other frameworks).
2) Ilia should be able to give you a better spec overview, but we we’re generally trying to be as stack agnostic as sanely physically possible. Roboticists have really strong preferences when it comes to hardware (often shaped by which components previously ruined demos in their life), and we want to be able to work with whatever you want to work with.
Reach out re:internships! No promises, but now that we have a stack you can build on for free that will definitely affect our decision process!
Might be a bit of a misunderstanding here. We’re not providing a sim world for you to do ML training on. Caladan would actually be a pretty terrible tool for that - it’s a static low-res environment without any other agents.
In Caladan we’re giving you a whole autonomous robot (in sim) that you can order around via a simple API.
In our use case the 5-10% that I’m talking about is really hard, but most teams / projects run out of funding before they get to that point (because making the robot, and making it autonomous, is so time and cost intensive it dominates the project).
In most robotics applications teams are building the equivalent of new speculative phone networks, building specialized infrastructure, acquiring specialized hardware companies to ease computer:phone connections, and running out of money before they can find product market fit for mass texting some sort of consumer.
Sure, they can still integrate Twilio poorly and fail. Or they can build a use case that no one cares about - but at least they won’t need 5 years to get to that point.
Thanks so much for the note and the kind words. Would love to grab a coffee or something! My email is first @ polymathrobotics.com, but I'll reach out as well!
This is a good, well thought out point that I 60% disagree with (respectfully, of course). I think you're absolutely accurate in describing how robotics is today, and you're definitely partially correct about how it will remain, but I think you're biasing towards thinking robotics (as a field) is exceptional to the types of progress that have happened in software.
To unfairly simplify that assertion, it reminds me of a founder who once told me that "robotics will never be as easy as software. It's just harder and will always be so."
I don't know if I think each autonomy company needs to figure out vehicle dynamics any more than I think each company needs to figure out their cloud infrastructure. At a certain scale (and amount of success) you will certainly need smart people thinking about it, but you can get pretty far on a 90% standard AWS instance. Things like wheel slippage are challenging, but their challenging in similar ways across vehicle types (but different from other tasks you need to work on when building that higher level autonomy).
Similarly, if you assume you can safely stop when there's danger, there are a relatively finite number of environmental conditions you should operate in - which we can build, maintain, and improve "once" as opposed to making every mining OEM or Ag autonomy shop build from scratch. In time, there might be certain portions of this stack that you can swap out with your own (or with some other company that's better at seeing in the fog, for example); but I fundamentally don't believe that every robotics company needs to solve all of these hard problems well on their own for every application.
Re:Sim - for paying customers we are putting their specific vehicle (and sometimes their environment) as a part of the offering. We're also using sim to help figure out how to position sensors (which will be another cool thing that we want to show at some point).
I only have experience working in the robotics field as it exists today, so you're right that I am probably unaware of how things are done in the software world. (I mean I read HN so I'm at least somewhat aware, but I don't have first hand experience of it in my work, so maybe I just don't know what I'm missing). So in that sense, I'm rooting for your success in launching this company -- it would help accelerate and expand the robotics field!
I think the way you're bounding your addressable problem space -- industrial vehicles operating in a closed environment -- makes a lot of sense. I also agree that certain classes of problems (like wheel slippage) would be better solved "once" by an expert team rather than repeatedly by people who are actually trying to solve a different problem of higher level autonomy as you put it.
Some random other thoughts:
- your business model and offering sound kinda similar to [Tangram Vision](https://www.tangramvision.com/about-tangram-vision), though not close enough to where you would be competitors. I'm not affiliated with Tangram at all, I've never even interacted with them, just sharing what I've come across in my research.
- How do you think about how your customers join and potentially leave your platform? In your reply you mention a certain scale and amount of success where companies may decide to start doing this themselves, or even going to other companies that specialize more than you do (e.g. Applied Intuition for sensor simulation). It might feel a bit early to think about on launch day, I'm just curious about how you think about your company's value prop for customers at different stages of growth. Are you potentially limiting your market to only niche segments and smaller players? Who is your key customer you're targetting?
I appreciate your response and candor, I'm very interested in seeing your company take off!
Thanks - appreciate that. And thanks for reading my response in the right tone (I was nervous no inflection might do me a disservice).
I’m not familiar with Tangram, but thanks for sharing. I’ll take a look!
There is definitely a world where customers “graduate out” of using Polymath, people do the same with Stripe (I know Uber has been at that decision point in the past). There’s probably a reasonable cap on how much we can charge a customer as a result (more likely pegged to the cost of 10-100 FT roboticists) and in time we’ll have to offer enterprise level SLAs.
So far we’ve seen traction with startups, tech consultants who are servicing big industrial co.s, OEMs, and the large industrial co.s themselves.
My hunch is that as we stop “doing things that don’t scale,” we’ll stop serving the big industrial companies themselves (and leave them to our other customer groups).
How does your stack integrate in with that of Rio Tinto?
They have, after all, been running remote and autonomous 100 tonne dump tracks and kilometre+ long trains for seven years now, in addition to being an umbrella across one of the largest mining fleets across the globe.
Hello,
Great question, I haven't seen enough technical details on their system to be able to answer definitely. However, from what I've read of their approach, it's fairly similar to the way we do things.
Perhaps this means there's no reason for Rio Tinto to use us, and that's totally fine. There are 1000s of other, much smaller mining companies that can benefit from the same tech, likely at a cheaper price than what Rio Tinto spent developing their own version.
Also, from our experience, these sort of approaches bake in assumptions on particular vehicle types/characteristics. So even in Rio's case, perhaps they have other smaller models, or other types of equipment they haven't automated. In this case, we'd be happy to integrate with their existing command and control software stack.
Rio has full fleet (bobcat, bulldozers, loaders, trains, underground mining speciality (uphole drillers, etc)) ambitions and they're working their way through them all.
Some of their talent date back to sheep shearing robots in the early 1980s.
In the same geographic region (W.Australia) there are related automata projects such as self recharging drone clouds about tractors, agri-bots (visual identification + weed spraying), integrated geophysical air survey, etc.
I was somewhat curious as to your awareness of all this (eg: Rio's plans for a full automated "bottom up" $64 billion copper mine in the US (should it go ahead)).
Also, while we're here, do you have any in house mining | industry experience driving tractors, dump trucks, ship loading, etc. yourselves?
I'd challenge this assertion. Rio Tinto has been on the forefront of automation, but there's a long list of equipment they operate that they don't have an immediate pathway to automate.
To my knowledge, the main players automating ultraclass mining trucks are Caterpillar, Komatsu, Hitachi, and ASI. CAT has been working on autonomy for a long time, and to my knowledge only offers full driver-out autonomy on a handful of models. Sandvik also has some really cool see-and-repeat autonomy in underground mining. It doesn't surprise me if Rio Tinto is talking about a full zero entry mine (worth it just because no people to hit = faster driving vehicles = more production/yr), but to my knowledge they buy their autonomy from others and no one I know of (besides us) would automate all the various types of equipment that go into running a mine.
A different large mining co had an initiative to build their own autonomy, but the project got cancelled when it wasn't making fast enough progress and the CEO was replaced with someone more Caterpillar friendly.
We don't have in house mining experience - but again we're not building autonomy just for mining. We're building generalized basic autonomy so the folks starting mining-specific autonomy projects don't get stuck re-building the basic autonomy wheel.
On a technical level, I'm not sure what sheep shearing robots in the 1980s has to do with automating vehicles... but I'd love to see a video/article if you've got one! :D
As with any large opportunity, there are multiple players in the space, both new and old. As seen with the "innovator's dilemma", I'm not sure I'd place my bets on tech straight out of the 1980/90s/2000s (sheep or no sheep ;) )
