Wen Dai

Nanjing University of Information Science and Technology, Carleton University

Papers

Total Citations

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About

Wen Dai is a researcher whose work bridges autonomous navigation, robotics, and real-time sensor fusion. Her key research areas include path planning optimization and multi-sensor tracking for mobile robots. In her most-cited work, a 2024 paper on the "passage time–cost optimal A* algorithm," Dai tackles a critical challenge in cross-country path planning for autonomous driving, logistics, and emergency rescue. By prioritizing passage time cost alongside distance, her algorithm improves efficiency in time-sensitive applications—a contribution that has already garnered 20 citations shortly after publication. Earlier, in 2008, Dai developed a real-time person tracking system for mobile robots, integrating PTZ video cameras with laser range finders. Her approach combined color, edge, and size information into a robust target model, enabling reliable tracking in dynamic environments. This work, with 16 citations, demonstrated early expertise in sensor fusion. Dai’s research is notable for its practical impact on autonomous systems, from logistics to rescue operations, and her ability to address real-world constraints like time optimization. Her trajectory from foundational tracking work to advanced path planning highlights a sustained focus on making robots more responsive and efficient in complex, unstructured environments.