Guanqun Liu

Dalian Minzu University, Harbin Engineering University

Papers

Total Citations

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About

Guanqun Liu’s research focuses on advancing robotic perception and human-robot interaction, with key contributions in sound source localization and rescue robotics. His most cited work, “A Sound Source Localization Method Based on Microphone Array for Mobile Robot” (2018, 8 citations), introduces a hybrid approach that integrates beamforming and time-difference-of-arrival techniques to enhance auditory localization for mobile robots. This method improves accuracy and robustness in noisy environments, addressing a critical challenge in robot hearing. Liu’s earlier study, “Research on Human–Robot Collaboration in Rescue Robotics” (2012, 2 citations), explores cooperative strategies for robots and humans in disaster scenarios, emphasizing intuitive communication and task-sharing to boost rescue efficiency. While his citation counts are modest, Liu’s work lays foundational groundwork for practical robotic audition and collaborative systems, bridging sensor technology and real-world deployment. His contributions are particularly relevant for researchers developing autonomous robots in dynamic, unstructured settings, such as search-and-rescue operations. Liu’s focus on microphone arrays and human-robot teamwork highlights his commitment to creating more perceptive and cooperative machines, offering valuable insights for students and engineers in robotics and artificial intelligence.