Li Chenghao, Seng Kah Phooi, Ang Li-Minn
School of Internet of Things, Xi'an Jiaotong-Liverpool University, Taicang 215000, China.
School of Science, Technology and Engineering, University of the Sunshine Coast, Petrie, QLD 4502, Australia.
Sensors (Basel). 2025 Jan 25;25(3):734. doi: 10.3390/s25030734.
The emotional response of robotics is crucial for promoting the socially intelligent level of human-robot interaction (HRI). The development of machine learning has extensively stimulated research on emotional recognition for robots. Our research focuses on emotional gaits, a type of simple modality that stores a series of joint coordinates and is easy for humanoid robots to execute. However, a limited amount of research investigates emotional HRI systems based on gaits, indicating an existing gap in human emotion gait recognition and robotic emotional gait response. To address this challenge, we propose a Gait-to-Gait Emotional HRI system, emphasizing the development of an innovative emotion classification model. In our system, the humanoid robot NAO can recognize emotions from human gaits through our Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer (TS-ST) and respond with pre-set emotional gaits that reflect the same emotion as the human presented. Our TS-ST outperforms the current state-of-the-art human-gait emotion recognition model applied to robots on the Emotion-Gait dataset.
机器人的情感反应对于提升人机交互（HRI）的社会智能水平至关重要。机器学习的发展极大地推动了机器人情感识别的研究。我们的研究聚焦于情感步态，这是一种简单的模态，存储着一系列关节坐标，便于人形机器人执行。然而，基于步态的情感人机交互系统的研究数量有限，这表明在人类情感步态识别和机器人情感步态响应方面存在差距。为应对这一挑战，我们提出了一种步态到步态的情感人机交互系统，着重开发一种创新的情感分类模型。在我们的系统中，人形机器人NAO可以通过我们的轨迹感知和骨架图感知时空变换器（TS-ST）从人类步态中识别情感，并以反映与人类所呈现相同情感的预设情感步态做出回应。我们的TS-ST在情感步态数据集上优于当前应用于机器人的最先进的人类步态情感识别模型。
