Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans.

人类的交互行为在各类重复性任务中均受运动同步动力学规律的支配。这要求交互双方完成诸如节律性肢体摆动，乃至具有目标导向的手臂动作等行为。受人类交互的这一核心特征启发，我们提出了一种全新的概念与设计方法，用于在重复性联合动作任务中为机器人智能体(robotic agents)合成具备目标导向的同步行为。机器人智能体的任务由闭合运动轨迹描述，并被建模为极限环(limit cycles)，基于振荡器理论(oscillator theory)可从中推导得到瞬时相位变量。我们引入将轨迹分割为多个基元的事件，作为增强型同步模式的锚点。我们采用统一视角整合连续相位与离散事件，设计了一种可对上述推导得到的模式进行同步的连续动力学过程。与相位推导过程相反，我们同时解决了从行为动力学中生成目标导向运动的问题。我们将所提出的概念部署至拟人机器人(anthropomorphic robot)上进行实现。为验证该概念的有效性，我们设计并开展了一项实验：机器人与人类搭档共同完成一项典型的取放任务(pick-and-place task)。通过相位与事件同步的客观量化指标，我们成功验证了所设计交互行为的有效性。从本探索性研究的受试者处收集到的反馈表明，该交互行为为参与者带来了主观上愉悦的交互体验。研究结果表明，该同步概念在机器人智能体间的运动协调，以及类人智能体与人类之间的增强型社会交互领域均具备潜在应用价值。