Learning and comfort in human-robot interaction: A review

Weitian Wang, Yi Chen, Rui Li, Yunyi Jia

Research output: Contribution to journalReview articlepeer-review

37 Scopus citations


Collaborative robots provide prospective and great solutions to human-robot cooperative tasks. In this paper, we present a comprehensive review for two significant topics in human-robot interaction: robots learning from demonstrations and human comfort. The collaboration quality between the human and the robot has been improved largely by taking advantage of robots learning from demonstrations. Human teaching and robot learning approaches with their corresponding applications are investigated in this review. We also discuss several important issues that need to be paid attention to and addressed in the human-robot teaching-learning process. After that, the factors that may affect human comfort in human-robot interaction are described and discussed. Moreover, the measures utilized to improve human acceptance of robots and human comfort in human-robot interaction are also presented and discussed.

Original languageEnglish
Article number5152
JournalApplied Sciences (Switzerland)
Issue number23
StatePublished - 1 Dec 2019


  • Collaborative robotics
  • Human acceptance of robots
  • Human comfort
  • Human-Robot interaction
  • Learning from human demonstrations


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