用雙手扭開蓋子

摘要

在機器人技術中，用兩隻多指手操作物體一直是一個長期存在的挑戰，這歸因於許多操作任務具有豐富的接觸特性，以及協調高維度雙手系統所固有的複雜性。在這項研究中，我們考慮使用兩隻手扭開各種瓶子狀物體的蓋子的問題，並展示通過深度強化學習在模擬中訓練的策略可以有效地轉移到現實世界。通過對物理建模、實時感知和獎勵設計的新穎工程見解，該策略展示了在各種未見過的物體上的泛化能力，展示了動態和靈巧的行為。我們的研究結果作為深度強化學習結合模擬到現實轉移的有前景方法，用於應對前所未有複雜性的操作問題的有力證據。

English

Manipulating objects with two multi-fingered hands has been a long-standing challenge in robotics, attributed to the contact-rich nature of many manipulation tasks and the complexity inherent in coordinating a high-dimensional bimanual system. In this work, we consider the problem of twisting lids of various bottle-like objects with two hands, and demonstrate that policies trained in simulation using deep reinforcement learning can be effectively transferred to the real world. With novel engineering insights into physical modeling, real-time perception, and reward design, the policy demonstrates generalization capabilities across a diverse set of unseen objects, showcasing dynamic and dexterous behaviors. Our findings serve as compelling evidence that deep reinforcement learning combined with sim-to-real transfer remains a promising approach for addressing manipulation problems of unprecedented complexity.

用雙手扭開蓋子

Twisting Lids Off with Two Hands

摘要

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