Integration of Tracking, Re-Identification, and Gesture Recognition for Facilitating Human-Robot Interaction.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

For successful human-robot collaboration, it is crucial to establish and sustain quality interaction between humans and robots, making it essential to facilitate human-robot interaction (HRI) effectively. The evolution of robot intelligence now enables robots to take a proactive role in initiating and sustaining HRI, thereby allowing humans to concentrate more on their primary tasks. In this paper, we introduce a system known as the Robot-Facilitated Interaction System (RFIS), where mobile robots are employed to perform identification, tracking, re-identification, and gesture recognition in an integrated framework to ensure anytime readiness for HRI. We implemented the RFIS on an autonomous mobile robot used for transporting a patient, to demonstrate proactive, real-time, and user-friendly interaction with a caretaker involved in monitoring and nursing the patient. In the implementation, we focused on the efficient and robust integration of various interaction facilitation modules within a real-time HRI system that operates in an edge computing environment. Experimental results show that the RFIS, as a comprehensive system integrating caretaker recognition, tracking, re-identification, and gesture recognition, can provide an overall high quality of interaction in HRI facilitation with average accuracies exceeding 90% during real-time operations at 5 FPS.

Authors

  • Sukhan Lee
    Artificial Intelligence Department, Sungkyunkwan University, Suwon 16419, Korea.
  • Soojin Lee
    Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
  • Hyunwoo Park
    Department of Industrial and Systems Engineering, Dongguk University - Seoul, 30 Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea.