Runze Fan

Papers

Total Citations

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About

Runze Fan is a researcher advancing the intersection of computer vision and robotics, with a primary focus on semantic mapping and autonomous navigation. Their most cited work, "The Method of Static Semantic Map Construction Based on Instance Segmentation and Dynamic Point Elimination" (2021, 7 citations), introduces a novel approach that enables mobile robots to not only localize and map their surroundings but also to understand environmental content at a semantic level. By integrating instance segmentation with dynamic point elimination, Fan’s method significantly enhances a robot’s ability to interact intelligently with its environment—particularly in high-level human–computer interaction scenarios. This contribution addresses a critical challenge in Simultaneous Localization and Mapping (SLAM) systems: filtering out dynamic objects to build robust, static semantic maps. Though early in their career, Fan’s work demonstrates a clear impact on improving robot perception and scene understanding, laying groundwork for more context-aware autonomous systems. Their research holds promise for applications in service robotics, autonomous driving, and smart environments, where machines must interpret and respond to complex, changing surroundings.