用双手扭开盖子

摘要

在机器人技术中，用两只多指手操纵物体一直是一个长期存在的挑战，这归因于许多操纵任务的接触丰富性质以及协调高维度双手系统固有的复杂性。在这项工作中，我们考虑了用两只手扭转各种瓶子状物体的盖子的问题，并展示了使用深度强化学习在模拟中训练的策略可以有效地转移到现实世界。通过对物理建模、实时感知和奖励设计的新颖工程洞见，该策略展示了跨多样未见物体集的泛化能力，展示了动态和灵巧的行为。我们的研究结果是深度强化学习结合模拟到真实转移仍然是解决前所未有复杂性操纵问题的一种有前途的方法的有力证据。

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.

用双手扭开盖子

Twisting Lids Off with Two Hands

摘要

Support