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Isn't this the same as dobb-e? https://dobb-e.com/
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.
Is the title a reference to OK computer or is it just something you all came up with?
Isn't this the same as dobb-e? https://dobb-e.com/
Earlier quoted context omitted.
A lot of those movements are there to zero out the axes so that each movement starts from a known good position and orients itself against the camera. Usually there's a switch that, for example, senses when the body goes all the way to the bottom, which is the origin for the whole positioning system. Several other movements are for safety since it doesn't have a bunch of cameras and really complex logic for collision…
>A lot of those movements are there to zero out the axes so that each movement starts from a known good position and orients itself against the camera. Usually there's a switch that, for example, senses when the body goes all the way to the bottom, which is the origin for the whole positioning system. Ideally the "zeroing" should be done once when the robot "wakes up" or only once in a while, and there should be digi…
This is remarkable and could be life changing for the disabled, elderly, gamers, or profoundly lazy and their caretakers.
I forgot where I saw that, but generally, improving things for people with disabilities improves things for everyone, like making sidewalks wheelchair friendly helps parents with a stroller, or people carrying heavy stuff, walking with a cane, young children on bicycles, people who can't see well...
This is remarkable and could be life changing for the disabled, elderly, gamers, or profoundly lazy and their caretakers.
This is rad. I would totally buy a 25k robot if I could train it to fold and put away my laundry (serious)
You might have to buy a second one to this one for folding [1] [1] https://pantor.github.io/speedfolding/
It's cool but what's the point for a normal person? Useful for warehouses and manufacturing but I don't see myself ever needing such things
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>> improving things for people with disabilities improves things for everyone Everything has its limits. Many years ago I was involved in building a series of staircases in a rock climbing area inside a park. There were about a hundred steps in a handful of orientations to get from the parking lot over a rocky hill to the small valleys behind. The project was primarily to prevent trail erosion and falls. These steps…
In the US? I assume ADA was the kicker. A lot of folks even in government don’t realize the ADA isn’t unthinking. If the activity or environment doesn’t lend itself to accessibility it’s not required. Cutting a wheel chair ramp into a mountain face is a good example where the ADA wouldn’t apply because it’s impractical given the environment to do so. Even national parks only offer a subset set of activities ADA compl…
Rock climbing areas tend to be inaccessible or at least very rough terrain. Ironically, a vertical rock surface can be made accessible. There are actually many disabled climbers out there. But with a mixed dirt/rock/scree slope you basically need to install a mile-long ramp.
That's very cool. I have almost no experience with robotics, so excuse the silly questions: - How does it know what objects are? Does it use some sort of realtime object classifier neural net? What limitations are there here? - 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? - How well does it do if the object is hidden or obscured? Does it go look…
> - 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.