User fishbotics already answers a lot of these questions downstream, but just confirming it here as an author of the project/paper:
> - How does it know what objects are? Does it use some sort of realtime object classifier neural net? What limitations are there here?
We use Lang-SAM (https://github.com/luca-medeiros/lang-segment-anything) to do most of this, with CLIP embeddings (https://openai.com/research/clip) doing most of the heavy lifting of connecting image and text. One of the nice properties of using CLIP-like models is that you don't have to specify the classes you may want to query later, you can just come up with them during runtime.
> - Does the robot know when it can't perform a request? I.e. if you ask it to move a large box or very heavy kettlebell?
Nope! As it is right now, the models are very simple and they don't try to do anything fancy. However, that's why we open up our code! So the community can build smarter robots on top of this project that can use even more visual cues about the environment.
> - How well does it do if the object is hidden or obscured? Does it go looking for it? What if it must move another object to get access to the requested one?
It fails when the object is hidden or obscured in the initial scan, but once again we think it could be a great starting point for further research :) One of the nice things, however, is that we take full 3D information in consideration, and so even if some object is visible from only some of the angles, the robot has a chance to find it.
A large motivation behind this line of home-robot work for me is thinking about the elderly, people with disabilities, or busy parents who simply don't have enough time to do it all. I am personally hopeful that we can teach AI to take the jobs that no one wants rather than the jobs that everyone wants :)
Thank you! A large motivation behind this line of home-robot work for me is thinking about the elderly, people with disabilities, or busy parents who simply don't have enough time to do it all. I am personally hopeful that we can teach AI to take the jobs that no one wants rather than the jobs that everyone wants :)
It's always a trade-off! You could have more accurate sensors and motors that are more expensive, or you can have cheaper motors with no sensors and higher accumulated errors. Since this is more of a research project than a product, we went for a cheap robot with the slower-but-more-accurate approach.
The title has multiple meanings, some credits definitely should go to OK computer/radiohead, but also "OK Google" for controlling a home assistant, open-knowledge (OK) models, etc.
No, although it has some of the same people on the team (aka I'm the first author there, and my advisor is advising both projects :) )
The primary difference is that this is zero-shot (meaning the robot needs 0 (zero!) new data in a new home) but has only two skills (pick and drop); where Dobb-E can have many skills but will need you to give some demonstrations in a new home.
The mapping process can be done with any RGB-D cameras, we use an iPhone pro but any apple devide with AR-Kit should work. Once we have a sequence of RGB-D images with associated camera poses, we can just backproject the pixels (and any associated information, like CLIP embeddings) using the depth into voxels.
Thanks! We collect all the data and analyze it post-facto to see what may have caused the failure. For example, on the 5 trials you mentioned, the Realsense gave wrong depth on transparent or semi-transparent objects, and so the pointcloud generated from the robot's head camera was simply wrong.
Second that. Something I put out recently had an (admittedly video heavy) webpage that had 1TB of traffic over the past month. Cloudflare handled it for free for me, but at ArXiv’s scale it’s bound to be a problem.
I am glad you mentioned automobiles! They are among the most heavily engineered everyday product that we use every day, and this engineering and cost optimization has been going on for close to a hundred years now. So, I would read this same statement as "$20k and 100 years of engineering gets us a lot" rather than "$20k gets us a lot". I am hoping better engineering and the wonders of modern supply chains will get us a home robot at 1/10th of the current price when the time is right.
I'm sorry, should have been clearer. The Spot robot with a manipulator arm (which has been used in some home projects before, see [0]) I believe totals up to about $200K. The base robot is $75K, which is what you linked to. I mentioned that figure because that seemed more relevant.
Smaller robots are unfortunately limited in how much force/torque they can apply and how high they can reach, two factors that we found can severely limit the applicability of a home robot. As a result, unfortunately, we don't have much plans for extending to a smaller robot at this moment.
However, all of our designs are open source! So if you or someone else is interested, it could be a fun weekend project to design a "Stick" equivalent data collection tool for the XGO CM4. I would love to see how that turns out.
> For the iPhone with the depth sensor cinematic format from the standard camera app seem to contain depth/RGB/traj. Maybe a candidate format. Also it’s much easier to operate standard camera app.
I agree with you there. My impression was that the cinematic format is closed, unlike .r3d which is a bunch of open format files in a .zip. Do you know whether Apple has published the specs for the cinematic video format anywhere, or if there are there good libraries for handling it?
I am sorry, what problems are you facing? I tested it with Safari on both my phone and laptop just now and couldn't find an issue, so I would really appreciate it if you can reply here or (more appreciated) email me with images etc. on the email listed on my profile.
I much appreciate your heads up, and thank you for taking your time on this.
But the tl;dr is that building prototypes is pricey, and the cost should definitely come down once the community moves from prototyping to mass-producing robots.
Hello Robots (the company behind the Stretch robot we're using) is also trying to bootstrap and build a sustainable product rather than blitzscaling and burning out fast [0, 1, 2] for which I respect them a lot. It's all too common of a story in robot world where have a great company showing lots of promise and then a year or two later they shut down after burning through investor money. I don't want to see it repeat.