Teerachart Soratana

Papers

Total Citations

H-Index

About

Teerachart Soratana investigates the intersection of human-robot collaboration and cognitive ergonomics, with a focus on how humans interpret and predict robotic intentions during physical tasks. His most cited work, “Human Prediction of Robot’s Intention in Object Handling Tasks” (2021, 3 citations), demonstrates that trained human workers can anticipate a robot’s future actions by observing its movement patterns—a finding that bridges the gap between human intuition and machine behavior. This research is pivotal for designing predictable, safer, and more intuitive human-machine teams, particularly in manufacturing and logistics. Soratana’s contributions lie in identifying how movement predictability can enhance team fluency and reduce cognitive load, offering a framework for improving interactive robotics. While his citation count reflects a growing niche, his work is foundational for researchers exploring non-verbal communication in collaborative robotics. By emphasizing the role of human training and pattern recognition, Soratana advances the practical deployment of robots that work seamlessly alongside people, making his research a valuable resource for students and engineers aiming to build more responsive and trustworthy autonomous systems.