Jing Yuan

National Institute of Informatics, Liaoning University, Nanjing University

Papers

Total Citations

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About

Jing Yuan is a researcher specializing in mobile robotics, computer vision, and wireless sensor networks, with contributions spanning autonomous navigation, simultaneous localization and mapping (SLAM), and real-time rescue systems. Their work addresses fundamental challenges in robotics and networked systems, with a particular focus on practical, real-world implementation. Yuan's early research laid groundwork in hybrid sensor network architectures, notably the DREAM framework (2010), which examined reaction delays in large-scale wireless networks integrating stationary and mobile sensors. This was followed by a real-time rescue system (2011) that combined sensor networks with autonomous robot navigation to guide victims through emergencies — a timely contribution to safety-critical robotics. Their most-cited work (2012) tackled the persistent challenge of feature recognition under complex lighting conditions using QR code-based robot action, garnering 9 citations and demonstrating a practical approach to robot-environment interaction. More recently, Yuan has advanced the state of SLAM technology by proposing a laser radar and vision fusion algorithm with loop detection optimization (2022), addressing the well-known limitations of single-sensor approaches. Across their body of work, Yuan demonstrates a consistent commitment to bridging theoretical robotics research with deployable, real-world solutions.