Advances in robotics have been driving the development of human-robot interaction (HRI) technologies. However, accurately perceiving human actions and achieving adaptive control remains a challenge in facilitating seamless coordination between human and robotic movements. In this paper, we propose a hierarchical procedural framework to enable dynamic robot-assisted hand-object interaction. An open-loop hierarchy leverages the computer vision (CV)-based 3D reconstruction of the human hand, based on which motion primitives have been designed to translate hand motions into robotic actions. The low-level coordination hierarchy fine-tunes the robot's action by using the continuously updated 3D hand models. Experimental validation demonstrates the effectiveness of the hierarchical control architecture. The adaptive coordination between human and robot behavior has achieved a delay of $\leq 0.3$ seconds in the tele-interaction scenario. A case study of ring-wearing tasks indicates the potential application of this work in assistive technologies such as healthcare and manufacturing.

翻译：机器人技术的进步不断推动着人机交互（HRI）技术的发展。然而，在促进人与机器人运动之间的无缝协调方面，准确感知人类动作并实现自适应控制仍然是一个挑战。本文提出了一种分层程序框架，以实现动态的机器人辅助手-物交互。开环层次利用基于计算机视觉（CV）的人手三维重建技术，并在此基础上设计了运动基元，以将人手动作转化为机器人动作。低层协调层次则通过持续更新的三维手部模型对机器人动作进行微调。实验验证证明了该分层控制架构的有效性。在远程交互场景中，人与机器人行为的自适应协调实现了延迟≤0.3秒的性能。一项佩戴戒指任务的案例研究表明，这项工作在医疗保健和制造等辅助技术领域具有潜在的应用前景。