Real-Time Adaptive Industrial Robots: Improving Safety And Comfort In Human-Robot Collaboration

TL;DR

This paper introduces a real-time adaptive industrial robot system that enhances safety and comfort in human-robot collaboration by monitoring physiological signals and adjusting robot behavior accordingly.

Contribution

It presents a novel user-aware robotic system that adapts to operator behavior and physiological signals in real time, improving collaboration and safety.

Findings

Adaptive system reduces perceived cognitive load

Participants felt more comfortable and trusting

System enhances collaboration quality

Abstract

Industrial robots become increasingly prevalent, resulting in a growing need for intuitive, comforting human-robot collaboration. We present a user-aware robotic system that adapts to operator behavior in real time while non-intrusively monitoring physiological signals to create a more responsive and empathetic environment. Our prototype dynamically adjusts robot speed and movement patterns while measuring operator pupil dilation and proximity. Our user study compares this adaptive system to a non-adaptive counterpart, and demonstrates that the adaptive system significantly reduces both perceived and physiologically measured cognitive load while enhancing usability. Participants reported increased feelings of comfort, safety, trust, and a stronger sense of collaboration when working with the adaptive robot. This highlights the potential of integrating real-time physiological data into human-robot interaction paradigms. This novel approach creates more intuitive and collaborative industrial environments where robots effectively 'read' and respond to human cognitive states, and we feature all data and code for future use.