‘Moonwalkers’: These Strappy Shoes Can Make You Walk Three Times Faster



Imagine being able to run a quick grocery errand or walk your dog as fast as if you were on a treadmill.

An American start-up, Shift Robotics, has invented a device designed to be attached to your own shoes to increase your walking speed by up to 250%.

That’s right, you could walk up to 11 km/h, about three times faster than you normally would.

The “Moonwalkers” look like skates, but they are not freewheeling – so as not to lose your balance.

Thanks to machine learning algorithms, they only move when you do: they can stop when you want, be locked to go up or down stairs, and automatically regulate their speed when you go down.

Suppose you are about to get on the bus: all you have to do is lift your right heel and then put it back on the ground so that the electronic brake completely locks the wheels.

To return to walking at a running pace, you get out of this “lock mode” by lifting your right heel in the air and rotating it clockwise while keeping your toe on the ground .

“Improve walking, don’t replace it”

Company founder Xunjie Zhang said the idea for his invention came after a near miss on his scooter on his way to work.

“I’ve wondered why I never walk to work – and it’s not just me, a lot of people don’t rely on walking, which is surprising considering it’s so much safer, easier and more convenient, and it’s better for the environment,” Zhang said in a statement.

“The problem is that walking is just too slow and inefficient. So I made it my mission to improve walking instead of replacing it.”

Along with a team of jet propulsion engineers at Carnegie Mellon’s Robotic Institute and roboticists and sneaker designers, Zhang has spent the past five years trying to design the world’s fastest shoes “based on the body engineering.

Shift Robotics says that unlike skating, Moonwalkers don’t require any skill to learn – it’s really walking.

According to the company, the AI ​​adapts to each user’s gait and it takes less than 10 steps for the algorithms to learn the user’s walking habits.

For more on this story, watch the video in the media player above.

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