Gait-to-Gait Emotional Human-Robot Interaction Utilizing Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

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.

Authors

  • Chenghao Li
    Product Development Department, FAW Car Co., Ltd, Changchun, China.
  • Kah Phooi Seng
    School of AI and Advanced Computing, Xian Jiaotong Liverpool University, Suzhou 215123, China.
  • Li-Minn Ang
    School of Science, Technology and Engineering, University of the Sunshine Coast, Petrie, QLD 4502, Australia.