Read Hayes

Papers

Total Citations

H-Index

About

Read Hayes is a pioneering researcher at the intersection of human-robot interaction (HRI) and retail automation. His work focuses on understanding how people naturally adjust their motion and behavior when sharing workspaces with mobile robots, particularly in dynamic retail environments. Hayes’s most influential paper, “Human Mobile Robot Interaction in the Retail Environment” (2022, 25 citations), introduces a novel dataset capturing real-world human-robot encounters during order picking and inventory tasks. This work is foundational for designing robots that can safely and intuitively collaborate with human workers. His follow-up study, “How Do Humans Adjust Their Motion Patterns in Mobile Robots Populated Retail Environments?” (6 citations), quantifies the subtle physical adaptations people make—such as path deviations and speed changes—when robots approach, providing critical insights for developing predictive motion models. By bridging robotics, cognitive science, and retail logistics, Hayes’s research directly informs the next generation of autonomous systems that must operate seamlessly alongside humans. His contributions are essential for creating safer, more efficient, and socially acceptable robots in commercial spaces.