From Action Perception to Joint Actions: Learning from Joint Handover Actions of Human Dyads for Robotic Actions and Human-Robot interactions (A01)

本研究的目的是探讨在交接任务中，人与人之间的联合行动协调。对联合行动控制的洞察可以推进混合（即，机器人-人）二人组。在我们的实验中，当系统地改变成对体的组成时，我们测量了在交接任务期间到达和抓握的运动学以及抓握力动态（例如，年龄的合作伙伴）和属性的对象（WP 1 -3）。高级分析（例如，降维）将用于理解到达和抓握运动学（WP 4 -6），因此，预测动作后果（例如，切换位置、力缩放），这便于联合动作。动作预测将在（WP 7）中进行模拟和测试。

The objective of this project is to investigate joint action coordination in human dyads during handover tasks. Insights into joint action control can advance control mechanisms for joint actions in mixed (i.e., robot-human) dyads. In our experiments, we measure kinematics of reach and grasp as well as grasp force dynamics during handover tasks when systematically varying the composition of the dyads (e.g., age of the partners) and properties of the objects (WP1-3). Advanced analysis (e.g., dimensionality reduction) will be used to understand reach and grasp kinematics (WP4-6) and, therefore, predict action consequences (e.g., handover position, force scaling), which facilitates joint action. Action prediction will be simulated and tested in (WP7).