论文标题
学习，产生和调整波浪手势以表达人类机器人的互动
Learning,Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction
论文作者
论文摘要
这项研究提出了一种新型的模仿学习方法，用于使用人类示范中的关节角度数据通过概率表述，通过概率表述，通过概率表述进行了类似人类的节奏波手势及其调节。这是通过学习和调节频域中手势的总体表达特征（例如手臂姿势，挥动频率和振幅）来实现的。在模拟机器人实验上评估了该方法，该实验涉及具有6个自由度的机器人的机器人。结果表明，该方法提供了节奏运动的有效编码和调制，并确保其执行变异性。
This study proposes a novel imitation learning approach for the stochastic generation of human-like rhythmic wave gestures and their modulation for effective non-verbal communication through a probabilistic formulation using joint angle data from human demonstrations. This is achieved by learning and modulating the overall expression characteristics of the gesture (e.g., arm posture, waving frequency and amplitude) in the frequency domain. The method was evaluated on simulated robot experiments involving a robot with a manipulator of 6 degrees of freedom. The results show that the method provides efficient encoding and modulation of rhythmic movements and ensures variability in their execution.
