Zeyu Tian

Papers

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About

Zeyu Tian is a researcher in mobile robotics, with a primary focus on autonomous exploration and simultaneous localization and mapping (SLAM) in unknown indoor environments. His work addresses a fundamental challenge in robotics: enabling robots to efficiently navigate and construct accurate maps of partially observable, uncertain spaces without prior knowledge. Tian’s major contributions include developing an improved Rapidly-exploring Random Tree (RRT) method for autonomous exploration and SLAM, which enhances a robot’s ability to make effective decisions in real-world, complex settings. His most cited paper, “An Improved RRT Robot Autonomous Exploration and SLAM Construction Method” (2020), has garnered 13 citations, demonstrating its relevance to the field. Additionally, his work on “Autonomous exploration of RRT robot based on seeded region growing” (2020, 5 citations) explores how to build high-quality maps during the exploration process itself, further advancing the efficiency and robustness of robotic mapping. Tian’s research is particularly valuable for applications in search-and-rescue, domestic service, and industrial automation, where reliable autonomous navigation is critical.