Understand how people work with robots
Human-AI interaction

Understand how people work with robots

Use eye tracking to reveal how people direct attention as they interact, coordinate, and share tasks with robots in real and simulated environments. 

Add human perspective to robotics

Robots can record their movements, commands, position, and task state. Eye tracking reveals what the person was attending to throughout the interaction. 

Investigate when people look toward a robot, monitor its movements, search for information, anticipate actions, or shift attention between the robot, task, and surrounding environment. 

Add human perspective to robotics

Benefits

Benefits

Turn human insight into more effective collaboration

Use gaze data to uncover how people respond to robotic systems, helping teams shape safer, more intuitive, and better coordinated ways of working together.

  • Guide attention effectively

    See how people interaction with the robot, task, or surrounding information to design clearer cues and more intuitive interactions.

  • Enable smoother coordination

    Identify how people and robots exchange visual information during shared tasks to support more seamless collaboration.

  • Hazards attract attention

    Discover whether robot movements, warnings, and potential hazards receive attention when needed to inform safer shared environments.

  • Shape more intuitive robot behavior

    Compare how movements, feedback, and interfaces influence attention to help robots communicate their actions more clearly to people.

  • Support appropriate reliance

    Combine gaze with performance and self-reported measures to understand how people monitor robots, respond to their actions, and decide when to intervene.

  • Optimize team performance

    Reveal how attention and responsibilities shift during shared tasks to identify opportunities for more effective team performance.

Applications

Applications

Eye tracking across human-robot interaction research 

Study how people attend to and interact with robots across industrial, mobile, assistive, and simulated environments. 

Collaborative and industrial robots 
Collaborative and industrial robots 
Collaborative and industrial robots 
Collaborative and industrial robots 

Investigate visual attention as people work alongside robotic systems, automation, and collaborative robots in shared workspaces. 

Mobile and autonomous robots 
Mobile and autonomous robots 
Mobile and autonomous robots 
Mobile and autonomous robots 

Study how people monitor and respond to autonomous or remotely operated robots moving through shared environments.  

Assistive and service robots 
Assistive and service robots 
Assistive and service robots 
Assistive and service robots 

Explore visual behavior as people interact with robotic systems designed to support users in healthcare, home, service, or public environments. 

Robot interfaces and feedback 
Robot interfaces and feedback 
Robot interfaces and feedback 
Robot interfaces and feedback 

Evaluate displays, indicators, controls, augmented information, and other ways robots communicate status and intent. 

Simulation and VR 
Simulation and VR 
Simulation and VR 
Simulation and VR 

Investigate human-robot interaction under controlled and repeatable conditions before or alongside physical testing. 

Research insights

Research measures

What you can measure 

Turn gaze behavior into measurable data to investigate how people monitor robots, coordinate attention, and respond throughout an interaction. 

  • Attention distribution 

    Measure how visual attention is divided between the robot, task, environment, and other sources of information. 

  • Gaze transitions 

    Investigate when and how attention shifts between the robot and other elements throughout an interaction. 

  • Fixations and dwell time 

    Measure which robot features, movements, objects, interfaces, or areas of the environment receive attention and for how long. 

  • Areas of interest 

    Define relevant areas around robots, interfaces, task objects, or environmental features and compare attention across conditions. 

Data integration

Connect gaze with robot and task data 

Synchronize visual attention with robot state, system events, task performance, video, motion, and other measures to understand what was happening when attention changed. 

Relate gaze to robot behavior 

Investigate where someone was looking before, during, and after robot movements, warnings, task changes, or other events. 

Connect attention with performance 

Relate visual behavior to task outcomes, response times, errors, interventions, and other performance measures. 

Combine multiple data streams 

Bring gaze together with robot data, video, motion, physiological signals, or other research measures for a richer view of the interaction. 

Connect gaze with robot and task data 

Our technology

Our technology

Eye tracking technology for human-robot interaction research

Choose glasses or screen-based eye tracking based on the robot, environment, and interaction you want to investigate. 

Not sure which setup fits your research?

Talk to our team about your study design, research environment, and measurement requirements.

Other solutions

Explore more ways people engage with technology

Bring eye tracking into your research

We can help you find the right eye tracking solution to study how people interact, coordinate, and share tasks with robots.

Use cases

See how researchers study human-robot collaboration

FAQs

Quick answers

Discover eye tracking in human-robot interaction

Find answers about using eye tracking to investigate attention, coordination, safety, and behavior as people interact with robots. 

Resources & community

Resources & community

Everything you need to get started

Free training, open-source tools, and direct support, designed to get you from unboxing to publishable results as fast as possible.

  • Tobii Academy

    Free online learning platform with structured courses covering every stage of eye tracking research, from fundamental concepts to advanced analysis techniques.

    → Eye tracking fundamentals and methodology

    → Experiment design best practices

    → Tobii Pro Lab software training

    → Data analysis and interpretation

    → Certification tracks

  • Open-source research tools

    50+ community-curated tools, experiment scripts, and integration libraries across the full eye tracking workflow. PsychoPy, MATLAB, Python, LSL, and more.

    Curated catalogue

    PsychoPy integration

    Tobii GitHub

  • Tobii Connect support portal

    Knowledge base, firmware updates, troubleshooting guides, and direct support from Tobii's technical team. Your first stop for any hardware or software question.

    → Product setup and troubleshooting guides

    → Firmware and software downloads

    → Data quality methodology documentation

    → Direct ticket support for registered products

    → Sample projects and demo recordings