101–110 of 195 posts
I'm sure this is impressive for an autonomous robot. However, as a fan of real parkour its kinda annoying to see some modest jumps and walking on a slope labelled "extreme parkour". What the robot demonstrates I'd expect any healthy 10 year old to be able to equal.
Whilst a lovely achievement, this title definitely overstates current robot abilities. Here is some human parkour for contrast: https://m.youtube.com/watch?v=QHqAVaQqQWQ&t=106s
Where did they buy this robot dog from? It looks like the Boston Dynamics one.
Like the whole point of saying “extreme” parkour is to boost engagement from pedantic analytic people like us talking about the hyperbolic title choice
It’s pretty incredible how animalistic its behaviors are becoming (hesitating for a moment at the edge of a lip, coiling it’s back legs for increased actuation, and when it almost misses the high jump and moves its back leg really fast multiple times to give itself a tiny boost each time until it recovers). Is that because it’s trained on animal behaviors? Or is this emergent behavior and animals just also do it more…
" A single neural net policy operating directly from a camera image, trained in simulation with large scale RL, can overcome imprecise sensing and actuation to output highly precise control behavior end-to-end. " So that's what it takes. That's so much simpler than the way Boston Dynamics does it, working out all the dynamics in simulation first. It's amazing to see this done from vision to actuators in one net. It's…
A very recent development (which this work builds on) is the idea of "online adaptation". It essentially involves doing the training in two stages:
1. You add a variety of dynamically-varying environmental effects to your simulator, by randomly altering parameters such as ground friction, payload weight distribution, motor effectiveness, and so on. You give the motion controller perfect knowledge of these parameters at all times, and let it learn how to move in response to them.
2. Then, you remove the oracle that tells the controller about the current environmental parameters, and replace it with another neural network that is trained to estimate (a latent representation of) those parameters, based on a very short window of data about the robot's own motor commands and the actual motion that resulted from it.
All of this can be done in simulation, many times faster than real-time. But when you transfer the system to a real robot, it adapts to its environment using the estimated parameters, without any of the networks needing to be re-trained. This ends up making it pretty robust to difficult terrain and perturbations. It also has the benefit of papering over subtle differences that arise between the simulated and real-world dynamics.
This paper adds a lot of additional refinements to the same basic idea. In the first stage, the system is given perfect knowledge of its surrounding terrain and the locations of some preselected waypoints, and learns to follow them. The second stage replaces those inputs with estimates derived from an RGB+depth camera.
Whilst a lovely achievement, this title definitely overstates current robot abilities. Here is some human parkour for contrast: https://m.youtube.com/watch?v=QHqAVaQqQWQ&t=106s
The difference being each human has to spend thousands of hours learning that level of control over their bodies, and work hard to maintain that level of physical fitness. And if they fall off the roof, millions of dollars of potential earnings and GDP die with them. Whereas these robots are only $70k, and once one of them can do this, they all can do it. Just like with Chess and Go. It’s not impressive at first, the…
This gives me Black Mirror-fueled nightmares... not least because those videos suggest that a Black Mirror scenario may not be that far off and what probably saves us for now is battery capacity.
Ideally, the panacea to such nightmares is democracy. In practice, history shows that greedy people with power often don't understand anything other than force (sadly).
Come on man, this is delusional. I want to believe it too but be realistic.
I am always wondering, why they build such complicated biology inspired robots, while they can build something with wheels and simple levels which allows robot to jump over obstacles and turn upside down if it landed on the back.