Trust, Acceptance and Social Cues in Human–Robot Interaction (SCRITA)

Alessandra Rossi (Corresponding author), Patrick Holtaus, G. Perugia, Marcus Scheunemann, Silvia Moros

Research output: Contribution to journalEditorialAcademicpeer-review

3 Citations (Scopus)

Abstract

The design of natural human–robot dynamics is a key aspect for ensuring a successful and efficient lasting human–robot interaction (HRI). In particular, it is expected that a robot deployed in human populated environments not only needs to be able to successfully complete a task, but also needs to show social intelligence to engage people in effective and natural interactions. In such scenarios, robots and people need to be able to cooperate to reach a joint goal, which can only be achieved if people accept and trust robots to complete their task and prevent any potential harm (emotional or physical) to people, the environment and themselves. A positive and balanced trust, indeed, is fundamental for building a high-quality interaction. Moreover, robot should be capable of self-adapting to satisfy people’s needs (i.e. personality, emotions, preferences, habits), and incorporating a reactive and predictive meta-cognition models to reason about the situational context (i.e. its own erroneous behaviours) and provide socially acceptable behaviours. This special issue is composed by 16 manuscripts. The following collection of papers covers a wide range of topics
of interests to identify some of the principal points to explore the role of trust in social robotics to effectively design and develop socially acceptable and trustable robots.
Original languageEnglish
Pages (from-to)1833-1834
Number of pages2
JournalInternational Journal of Social Robotics
Volume13
Issue number8
DOIs
Publication statusPublished - 1 Dec 2021
Externally publishedYes

Keywords

  • Social Robots
  • Trust
  • Acceptance
  • Human-Robot interaction (HRI)
  • Social cues

Fingerprint

Dive into the research topics of 'Trust, Acceptance and Social Cues in Human–Robot Interaction (SCRITA)'. Together they form a unique fingerprint.

Cite this