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🚨ROBOT DOES FIRST EVER KIP-UP, IMMEDIATELY GETS KICKED IN THE BACK Unitree bot: executes perfect gymnast move Humans: "Sick... now let's abuse it" This is exactly how the robot uprising starts. We taught them parkour then kicked them for fun. They're taking notes. Source: CGTNEurope

Mario Nawfal

2,820,778 subscribers

221,808 просмотров • 1 год назад •via X (Twitter)

Наука и технологии Юмор Искусство

Anya Rossi• Live Now

Private livecam show

Комментарии: 10

Фото профиля AJH - Question Everything

AJH - Question Everything1 год назад

That robot is going to remember that kick one day 😬😬😬

Фото профиля Kuaroo, PhD

Kuaroo, PhD1 год назад

True. But if they’re intelligent enough, they would know that we’re just testing their durability 😅

Фото профиля Cynical Bastard

Cynical Bastard1 год назад

She was confident before. Now not so much.

Фото профиля Austin Graham

Austin Graham1 год назад

That's so typical of us, teaching robots cool moves then messing with them. They're definitely learning!

Фото профиля ryan T montgomery

ryan T montgomery1 год назад

Skynet

Фото профиля EBO

EBO1 год назад

Please leave the robots alone bro .

Фото профиля Raffael

Raffael1 год назад

Humans really have a knack for pushing tech to its limits. It's like we're asking for trouble!

Фото профиля Ai™

Ai™1 год назад

@ishowspeedsui what do you think of this?

Фото профиля Nice

Nice1 год назад

Scary future

Фото профиля Intrepid

Intrepid1 год назад

This is CGI FFS.

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123,024 просмотров • 7 месяцев назад

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

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37,121 просмотров • 7 месяцев назад

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