Qingjun Wang

Nanjing University of Aeronautics and Astronautics, Shenyang Aerospace University

Papers

Total Citations

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About

Qingjun Wang is a pioneering researcher at the intersection of cognitive robotics, brain-computer interfaces, and next-generation wireless networks. His work focuses on endowing robots with human-like emotional cognition—a critical factor for achieving truly friendly and intuitive human-robot interaction. Wang’s most influential contribution, "Control method of robot detour obstacle based on EEG" (2021, 11 citations), demonstrates a novel approach to integrating electroencephalography signals for real-time robotic navigation, allowing machines to interpret neural commands for obstacle avoidance. Expanding on this, his study "Cognitive Robotics on 5G Networks" (2021, 7 citations) explores how ultra-low-latency 5G communication can enable robots to process and respond to emotional cues in dynamic environments, effectively merging affective computing with advanced connectivity. By framing emotional cognitive ability as a key technical indicator for interaction quality, Wang has laid foundational groundwork for socially aware autonomous systems. His research not only advances the technical capabilities of cognitive robots but also addresses the growing demand for empathetic, responsive machines in healthcare, service, and collaborative industrial settings.