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Don't get distracted by the specific task. The task is analogous to Hinton's neural networks doing handwritten digit recognition. It's a placeholder task while
by robotresearcher 4y ago
Don't get distracted by the specific task. The task is analogous to Hinton's neural networks doing handwritten digit recognition. It's a placeholder task while the tech evolves. Not too easy, not too hard. Not crazy, has some value, but not claiming to be a killer app. The robot is doing mobile manipulation in a semi-structured environment that was not designed for the robot: this has been in the 'tough' category for a long time.
It's also a clear nod to Connell's Herbert, from nearly 40 years ago. A seminal project in AI/robotics history.
https://cyberneticzoo.com/cyberneticanimals/1986c-herbert-the-collection-machine-brooks-connell-ning-american/ https://cyberneticzoo.com/cyberneticanimals/1986c-herbert-th...
- modeless 4y agoThe analogy is apt but I don't come to the conclusion that this is the right way to attack the problem of general robotics. One of the principal lessons of the rise of neural nets is that hardware is supremely important. Neural nets would have remained toys for decades more if it wasn't for GPUs. I see a slow and limited robotic platform like this as analogous to CPU-only neural nets. We were lucky that GPUs developed for other purposes were perfect for neural nets, and then Nvidia went all-in early on hardware to enable the rise of deep learning. But I don't think robotics will be the same. Unfortunately you're not going to magically find a perfect robot body that someone else already made for another purpose. If you want to make real progress in robotics you'll need to advance the state of the art in hardware by a lot and make something much more capable than this robot. If you're not doing that, you'll be passed by someone who does.