Yuliang Zhou

Papers

Total Citations

H-Index

About

Yuliang Zhou is a researcher specializing in human-robot interaction, intelligent perception, and swarm robotics. Their work focuses on bridging the gap between human intent and robotic action, with key contributions in natural interaction paradigms and augmented reality interfaces. Zhou’s most cited paper, “Intelligent grasping with natural human-robot interaction” (2017, 8 citations), proposes a method that integrates Kinect-based visual and voice data to enable robots to perform grasp tasks guided by human conduct, advancing intuitive human-robot collaboration. In a subsequent study, “A Human-swarm Interaction Method Based on Augmented Reality” (2018, 3 citations), Zhou addresses the challenge of controlling multiple robots by overlaying operational and environmental data via augmented reality, reducing operator cognitive load and enhancing swarm management. Though early in their career, Zhou’s work demonstrates a clear trajectory toward making robotic systems more accessible and responsive to human input, with potential applications in manufacturing, assistive technology, and multi-robot coordination. Their research is particularly relevant for students and researchers exploring the intersection of perception, control, and user-centered design in robotics.