両手でキャップをひねり開ける：双腕多指ハンドのsim-to-real強化学習
Twisting Lids Off with Two Hands
シミュレーションで深層強化学習を用いて訓練した双腕多指ハンドの制御方策を、物理モデリング・実時間知覚・報酬設計の工夫により実世界へ効率的に転移し、多様な未見のボトルキャップを両手でひねり開ける動的で器用な動作を実現した。
著者: Toru Lin, Zhao-Heng Yin, Haozhi Qi, Pieter Abbeel, Jitendra Malik
分類: cs.RO, cs.AI, cs.CV, cs.LG
原文アブストラクト
Manipulating objects with two multi-fingered hands has been a long-standing challenge in robotics, due to the contact-rich nature of many manipulation tasks and the complexity inherent in coordinating a high-dimensional bimanual system. In this work, we share novel insights into physical modeling, real-time perception, and reward design that enable policies trained in simulation using deep reinforcement learning (RL) to be effectively and efficiently transferred to the real world. Specifically, we consider the problem of twisting lids of various bottle-like objects with two hands, demonstrating policies with generalization capabilities across a diverse set of unseen objects as well as dynamic and dexterous behaviors. To the best of our knowledge, this is the first sim-to-real RL system that enables such capabilities on bimanual multi-fingered hands.
