Toward Socially Aware Person-Following Robots

Abstract
Significant R&D has been invested in technical issues related to person following. However, a systematic approach for designing robotic person-following behavior that maintains appropriate social conventions across contexts has not yet been developed. To understand why this may be the case, an in-depth literature review of 221 articles on person-following robots was performed, from which 107 are referenced. From these papers, six relevant topics were identified that shed light on the types of social interactions that have been studied in person-following scenarios: a) applications; b) robotic systems; c) environments; d) following strategies; e) human-robot communication; and f) evaluation methods. Gaps in the existing research on person-following robots were identified, mainly in addressing social interaction and user needs, noting that only 25 articles reported proper user studies. Human-related, robot-related, task-related, and environment-related factors that are likely to influence people’s spatial preferences and expectations of a robot’s person-following behavior are then discussed. To guide the design of socially aware person following robots, a user-needs layered design framework that combines the four factor categories is proposed. The framework provides a systematic way to incorporate social considerations in the design of person-following robots. Finally, framework limitations and future challenges in the field are presented and discussed.
Funding Information
  • Ministry of Science and Technology, Israel (3-12060)
  • Helmsley Charitable Trust through the Agricultural, Biological, and Cognitive Robotics Center, the Marcus Endowment fund through Ben-Gurion University of the Negev
  • Rabbi W. Gunther Plaut Chair in Manufacturing Engineering through Ben-Gurion University of the Negev
  • EU funded Innovative Training Network in the Marie Skłodowska-Curie People Programme (Horizon2020): Social Cognitive Robotics in a European Society Training Research Network (721619)