Qinghua Xiao

Tsinghua University, China University of Mining and Technology

Papers

Total Citations

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About

Qinghua Xiao is a robotics researcher specializing in autonomous navigation, human-robot interaction, and simultaneous localization and mapping (SLAM). Her work focuses on enabling mobile robots to perceive and interact with dynamic environments, particularly through human tracking and multi-sensor fusion. In her highly cited 2017 paper, "Human tracking and following of mobile robot with a laser scanner" (12 citations), she developed a robust method for detecting a person's legs using laser scanners, allowing robots to follow human targets reliably—a key capability for service and collaborative robots. She further advanced autonomous exploration in her 2017 work, "Robotic autonomous exploration SLAM using combination of Kinect and laser scanner" (3 citations), where she proposed a novel fusion of depth camera and laser data to improve mapping and exploration efficiency. Xiao’s contributions bridge critical gaps in real-world robotic deployment, combining practical sensor integration with intelligent control. Her research has direct applications in assistive robotics, warehouse automation, and human-robot teamwork, demonstrating how low-cost sensors can achieve high-performance autonomy.