Bimanual handovers are crucial for transferring large, deformable or delicate objects. This paper proposes a framework for generating kinematically constrained human-like bimanual robot motions to ensure seamless and natural robot-to-human object handovers. We use a Hidden Semi-Markov Model (HSMM) to reactively generate suitable response trajectories for a robot based on the observed human partner's motion. The trajectories are adapted with task space constraints to ensure accurate handovers. Results from a pilot study show that our approach is perceived as more human--like compared to a baseline Inverse Kinematics approach.

翻译：双臂交接对于转移大型、易变形或易碎物体至关重要。本文提出了一种框架，用于生成受运动学约束的类人双臂机器人运动，以确保机器人向人类无缝且自然地交接物体。我们使用隐半马尔可夫模型（HSMM）根据观察到的人类伙伴运动，反应性地生成机器人的合适响应轨迹。通过任务空间约束对轨迹进行调整，以确保交接的准确性。一项初步研究结果表明，与基线逆运动学方法相比，我们的方法被认为更类人。