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Today we’re introducing KinetIQ Ascend: our reinforcement learning approach designed to reach 99.9% manipulation reliability at human speed and beyond. It enables our robots to learn from real production tasks and improve through trial and error: • Machine feeding: throughput +42% • Item handover: throughput +85%, success from 80%...

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Humanoid

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43,326 просмотров • 3 месяцев назад •via X (Twitter)

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Фото профиля Humanoid
Humanoid3 месяцев назад

Learn more about KinetIQ Ascend:

Фото профиля Nick Venturi
Nick Venturi3 месяцев назад

meanwhile i still struggle to plug in a usb

Фото профиля Steven Cheng
Steven Cheng3 месяцев назад

99.9% reliability at human speed is wild.

Фото профиля SEAR
SEAR3 месяцев назад

99% reliability is wild

Фото профиля Tradeye
Tradeye3 месяцев назад

Imitation learning is only as good as the demonstrations. We capture narrated first-person video from licensed trades technicians doing real manipulation work inside occupied American homes — high-signal tool use and decision-making in messy, unstructured environments.

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Our model can now learn from its own experience with RL! Our new π*0.6 model can more than double throughput over a base model trained without RL, and can perform real-world tasks: making espresso drinks, folding diverse laundry, and assembling boxes. More in the thread below.
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Our model can now learn from its own experience with RL! Our new π*0.6 model can more than double throughput over a base model trained without RL, and can perform real-world tasks: making espresso drinks, folding diverse laundry, and assembling boxes. More in the thread below.

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