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June 27, 2026The International Journal of Robotics ResearchOpen Access

Computational models of artificial and natural trust in robotics: A systematic review and operational guide

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Authors

SVSamuele VinanziMRMarta RomeoACAngelo Cangelosi

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Overview

Systematic review identifies key trends and guidelines for computational trust models in robotics, suggesting improvements in human-robot collaboration.

Key Points

  • This review aims to explore computational trust models in robotic systems, focusing on both artificial and natural trust dynamics.
  • Reviewed 1916 papers from 2013 to 2023 from IEEE Xplore, Scopus, and ISI Web of Science.
  • Applied specific eligibility criteria to identify 101 papers that developed validated computational trust models.
  • Analyzed selected works based on model type, application domain, robotic platforms, experimental design, and evaluation metrics.
  • Identified key trends in computational trust models across various robotic applications.
  • Provided guidelines for future research to enhance human-robot trust and collaboration.

Cite This Study

Vinanzi et al. (2026) studied this question.

synapsesocial.com/papers/6a3f68f5aea7db3c1953fdefhttps://doi.org/10.1177/02783649261459131
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Comparisons of Human-Human Trust with Other Forms of Human-Technology Trust2017 · 13 citations
  2. 2Trust as a design principle in human–robot collaboration: a review of explainable and adaptive control2026 · 1 citations
  3. 3Converging Measures and an Emergent Model: A Meta-Analysis of Human-Machine Trust Questionnaires2024 · 3 citations
  4. 4Modelling and Measuring Trust in Human–Robot Collaboration2024 · 29 citations
  5. 5Modeling, Engendering and Leveraging Trust in Human-Robot Interaction: A Mental Model Based Framework2024