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No teleoperation. No simulation. No RL. Multi-fingered robot manipulation policies directly by watching videos of humans with Aria glasses on. It was super fun working on this with Irmak Guzey's lead!! 1/n

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Homanga Bharadhwaj

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51,532 просмотров • 7 месяцев назад •via X (Twitter)

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Three demos showing SharpaWave’s fine manipulation under high-fidelity teleoperation. Task No.1: putting on a trash bag. With teleoperation and tactile feedback, it finds the rim, opens it, and wraps it neatly — even on a slippery, deformable object. #Sharpa #SharpaWave #Teleoperation #Tactile #DexterousHand
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Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!
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