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TICK: A Knowledge Processing Infrastructure for Cognitive Trust in Human-Robot Interaction.

Mohammed Diab1, Yiannis Demiris1

  • 1Personal Robotics Laboratory, Imperial College London, South Kensington Campus, London, UK.

International Journal of Social Robotics
|December 29, 2025
PubMed
Summary
This summary is machine-generated.

A new Trust-Inferring Infrastructure for Cognitive Knowledge (TICK) framework enhances human-robot interaction by enabling shared knowledge and trust assessment. This system improves robot understanding and trustworthiness in real-world scenarios.

Keywords:
Human–robot interactionInteraction memoriesKnowledge-driven approachTrust infrastructure

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Cognitive Science

Background:

  • Assessing trust in human-robot interaction (HRI) is crucial for social and assistive robotics.
  • Existing systems lack a unified cognitive infrastructure for shared knowledge and trust evaluation.
  • The need for domain-agnostic solutions that promote trust in HRI is growing.

Purpose of the Study:

  • To introduce and evaluate the Trust-Inferring Infrastructure for Cognitive Knowledge (TICK) for HRI domains.
  • To develop a domain-agnostic ontology for shared knowledge encompassing behavior, beliefs, intentions, and situational awareness.
  • To enable participants to take actions that build trust with other parties in HRI.

Main Methods:

  • Developed a layered, domain-agnostic ontology for shared knowledge.
  • Introduced the TICK framework with three constructs: performance, process, and purpose.
  • Integrated a multimodal sensory module for enhanced robot reasoning and validated through real-world scenarios and lab experiments.

Main Results:

  • TICK enhances robot capabilities in understanding human intentions, situational awareness, and personalized behavior.
  • Robot trustworthiness evolved based on performance, with trust automatically assessed via proximity and recommendation adherence.
  • Experiments demonstrated the scalability and flexibility of TICK in a kitchen domain handover task.

Conclusions:

  • The TICK framework provides a robust cognitive infrastructure for assessing and building trust in HRI.
  • The multimodal sensory integration and layered ontology allow for adaptable and effective human-robot collaboration.
  • The study validates TICK's potential for diverse HRI applications requiring trust and shared understanding.