Hsien-Chan Lin

National Taiwan University of Science and Technology

Papers

Total Citations

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About

Hsien-Chan Lin is a researcher at the forefront of autonomous robotics and intelligent sensing systems. His work centers on advancing simultaneous localization and mapping (SLAM) technologies, particularly through the integration of evolutionary algorithms and LiDAR-based perception. In his most-cited paper, "Design and implementation of intelligent LiDAR SLAM for autonomous mobile robots using evolutionary normal distributions transform" (2023, 7 citations), Lin introduces a novel approach that enhances the accuracy and robustness of SLAM in dynamic environments. By applying evolutionary optimization to the normal distributions transform, his method enables mobile robots to navigate and map complex spaces with greater efficiency—a critical contribution to the fields of autonomous navigation and field robotics. This work not only demonstrates Lin’s ability to bridge theoretical optimization with practical robotic systems but also lays groundwork for more adaptive, real-time SLAM solutions. With a growing citation footprint, Lin is establishing himself as an emerging voice in intelligent robotics, and his research holds promise for applications in autonomous vehicles, warehouse logistics, and search-and-rescue operations.