ArticleSensors (Basel, Switzerland)2025
Collaborative Robot Control Based on Human Gaze Tracking.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A methodological framework and experimental protocol for proactive human-robot collaboration with multimodal intention prediction and adaptive control.Frontiers in robotics and AI · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gaze tracking is gaining relevance in collaborative robotics as a means to enhance human-machine interaction by enabling intuitive and non-verbal communication. This study explores the integration of human gaze into collaborative robotics by demonstrating the possibility of controlling a robotic manipulator with a practical and non-intrusive setup made up of a vision system and gaze-tracking software. After presenting a comparison between the major available systems on the market, OpenFace 2.0 was selected as the primary gaze-tracking software and integrated with a UR5 collaborative robot through a MATLAB-based control framework. Validation was conducted through real-world experiments, analyzing the effects of raw and filtered gaze data on system accuracy and responsiveness. The results indicate that gaze tracking can effectively guide robot motion, though signal processing significantly impacts responsiveness and control precision. This work establishes a foundation for future research on gaze-assisted robotic control, highlighting its potential benefits and challenges in enhancing human-robot collaboration.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.