Chen-Tung Chi

Taipei City University of Science and Technology

Papers

Total Citations

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About

Chen-Tung Chi’s research focuses on advancing robotic perception and autonomy, with a particular emphasis on visual simultaneous localization and mapping (vSLAM) in complex, real-world environments. His work addresses a critical challenge in robotics: enabling machines to build persistent maps and navigate reliably even when their surroundings are cluttered with moving objects. In his most-cited paper, “Robot mapping using local invariant feature detectors” (2014, 6 citations), Chi explored how visual landmarks detected through invariant features can create robust maps for SLAM systems, moving beyond traditional corner detectors to improve mapping stability. He further advanced the field with “Robot Visual Simultaneous Localization and Mapping in Dynamic Environments” (2012, 4 citations), where he introduced a moving object detection algorithm that leverages spatial geometric constraints of stationary landmarks. This innovation allows vSLAM systems to filter out dynamic elements—such as people or vehicles—enhancing both map accuracy and robot safety. Though his citation counts are modest, Chi’s contributions are foundational for researchers tackling real-world deployment of autonomous robots, where static assumptions often fail. His work remains a valuable reference for those developing resilient navigation systems in unpredictable settings.