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Related Experiment Video

Updated: Oct 8, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Trust in Robots: Challenges and Opportunities.

Bing Cai Kok¹, Harold Soh¹

¹Dept. of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore, 119077 Singapore.

Current Robotics Reports

|January 3, 2022

Summary

This summary is machine-generated.

Researchers are developing strategies for robots to actively build and maintain user trust. Recent advances in AI and ethics offer tools to create more trustworthy autonomous social robots for real-world interactions.

Keywords:

Formal methods Human-robot interaction Measurement Probabilistic models Trust

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Area of Science:

Robotics
Human-Robot Interaction (HRI)
Artificial Intelligence (AI)

Background:

Traditional research focused on understanding trust in robots.
Recent work emphasizes robots actively managing user trust.

Purpose of the Study:

Assess the current state of trust in robots research.
Examine how methodological advances can create trustworthy robots.

Main Methods:

Review of recent literature on trust in robotics.
Analysis of strategies for robots to gain, calibrate, and maintain trust.
Exploration of reasoning capabilities in robotic agents.

Main Results:

Shift from studying trust antecedents to active trust development strategies.
Emphasis on endowing robots with reasoning capabilities, such as probabilistic modeling.
Identification of challenges in real-world HRI: trust measurement, behavior guarantees, and data handling.

Conclusions:

The state-of-the-art offers tools for developing trustworthy robots.
Advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can address HRI challenges.
Methodological progress can lead to autonomous, trustworthy social robots.