MyoDex：一種適用於熟練操作的通用先驗

MyoDex: A Generalizable Prior for Dexterous Manipulation

September 6, 2023

作者: Vittorio Caggiano, Sudeep Dasari, Vikash Kumar

cs.AI

摘要

人類的靈巧性是運動控制的一個標誌。儘管肌骨感覺運動回路的複雜性（多關節和多關節，由40多個肌肉控制的23個關節） ，我們的手能夠迅速合成新的行為。在這項工作中，我們受到人類靈巧性如何建立在各種先前經驗基礎上的啟發，而不是通過單一任務獲得的。受到這一觀察的激勵，我們開始開發能夠建立在先前經驗基礎上以迅速獲得新的（以前無法達到的）行為的代理人。具體而言，我們的方法利用多任務學習來隱式捕捉人類靈巧性的任務不可知行為先驗（MyoDex），使用一個生理逼真的人手模型 - MyoHand。我們展示了MyoDex在少樣本泛化以及對大量未見靈巧操作任務的積極轉移中的有效性。利用MyoDex的代理人可以解決大約多3倍的任務，並比蒸餾基線方法快4倍。儘管以前的工作合成了單一的肌骨控制行為，但MyoDex是第一個通用的操作先驗，促進了對接觸豐富行為的大量靈巧生理控制的學習。我們還展示了我們的範式在肌骨控制之外對Adroit Hand的24個自由度靈巧性獲得的有效性。網站：https://sites.google.com/view/myodex

English

Human dexterity is a hallmark of motor control. Our hands can rapidly synthesize new behaviors despite the complexity (multi-articular and multi-joints, with 23 joints controlled by more than 40 muscles) of musculoskeletal sensory-motor circuits. In this work, we take inspiration from how human dexterity builds on a diversity of prior experiences, instead of being acquired through a single task. Motivated by this observation, we set out to develop agents that can build upon their previous experience to quickly acquire new (previously unattainable) behaviors. Specifically, our approach leverages multi-task learning to implicitly capture task-agnostic behavioral priors (MyoDex) for human-like dexterity, using a physiologically realistic human hand model - MyoHand. We demonstrate MyoDex's effectiveness in few-shot generalization as well as positive transfer to a large repertoire of unseen dexterous manipulation tasks. Agents leveraging MyoDex can solve approximately 3x more tasks, and 4x faster in comparison to a distillation baseline. While prior work has synthesized single musculoskeletal control behaviors, MyoDex is the first generalizable manipulation prior that catalyzes the learning of dexterous physiological control across a large variety of contact-rich behaviors. We also demonstrate the effectiveness of our paradigms beyond musculoskeletal control towards the acquisition of dexterity in 24 DoF Adroit Hand. Website: https://sites.google.com/view/myodex