Shang-Yen Lin

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About

Shang-Yen Lin is a researcher specializing in robotics and autonomous navigation, with a primary focus on Simultaneous Localization and Mapping (SLAM) for indoor environments. His work centers on developing robust perception systems that enable robots to understand and navigate complex indoor spaces using stereo vision. Lin's major contribution lies in his innovative approach to extracting 3D vertical line features from stereo camera images as landmarks, which he integrated into an Extended Kalman Filter (EKF)-based SLAM framework. By employing two distinct observation models to handle measurement uncertainty, he significantly improved the accuracy and reliability of robot localization in cluttered indoor settings. His most-cited paper, "SLAM for Indoor Environment Using Stereo Vision" (2010), has garnered 4 citations, while his subsequent work "SLAM and Navigation in Indoor Environments" (2011) has received 3 citations. Though modest in citation count, these foundational studies represent early efforts in applying stereo vision to SLAM challenges, paving the way for later advancements in visual-based autonomous navigation. Lin's research remains relevant for students and engineers exploring practical SLAM implementations in real-world indoor robotics applications.