Natinun Maneerung
Papers
1
Total Citations
2
H-Index
1
About
Natinun Maneerung is a researcher advancing the field of human-robot interaction, with a focus on enabling safer and more intuitive collaboration between mobile robots and people. Their key research areas include human detection, human pose classification, and autonomous navigation for mobile robots operating in dynamic environments such as hospitals, restaurants, and industrial settings. Maneerung’s most cited work, "Human Detection and Human Pose Classification for Mobile Robots Interaction" (2024, 2 citations), introduces a novel approach to classifying human poses specifically for collision avoidance during human-robot interaction. This contribution addresses a critical safety challenge: enabling robots to interpret human body language and movement in real time, thereby preventing accidents in shared spaces. By combining computer vision techniques with robotics, Maneerung’s research lays groundwork for more responsive and socially aware autonomous systems. Though early in their career, this work signals a commitment to bridging the gap between robotic perception and human-centered design—a vital step toward the widespread deployment of mobile robots in everyday environments.
Research Focus
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Top Papers
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