Robots Learn to Navigate Surroundings by Watching 2000 videos of the Mannequin Challenge


Remember the worldwide phenomenon: "Mannequin Challenge" a couple of years ago? It swept through like bushfire back in 2016, when everybody and your grandmother, were posting Mannequin Challenge videos like these?

Well, it turns out that aside from spawning other dance challenges/memes, the Mannequin challenge has been instrumental for Google researchers who are using the videos to help train robots to better navigate their surroundings.

While humans are naturally able to look at a 2D video and understand it was filmed in a 3D space, robots aren’t so good at that yet. That’s part of the reason why robots struggle to autonomously navigate new areas, and its also a challenge when it comes to building self-driving cars.

Turns out, the Mannequin Challenge presented the perfect data set for teaching robots how to perceive depth in a 2D image.

Of the unnumbered videos uploaded to YouTube, the researchers selected 2,000 of them. They then filtered the clips to remove those unsuitable for training—if someone, say, unfroze, used fisheye lenses, or had synthetic backgrounds that could lead to borked results. The final data set was then used to train a neural network that could predict the depth of a moving object in a video. According to the paper’s conclusion, accuracy was much higher using this method than previous state-of-the-art methods.

There are some limitations, however. The researchers noted that their method may not be quite so accurate when it comes to cars and shadows. However, they did make their data set public. So, how do you know if your particular Mannequin Challenge video was used in the set? Short answer is: You won’t.

According to MIT Technology Review, which initially reported on the study, AI researchers commonly scrape publicly available images to train bots. And the more advanced the models researchers use, the more data they need to train the neural networks. So if you upload a video to YouTube, and an AI researcher happens to think it helps teach a neural network how to better navigate, well, you uploaded your video and made it publicly available.

So if you think you're just doing something for the sake of silly three years ago, think again. You might've helped robots come closer to taking over the world! Just kidding!


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