Long-Jye Sheu

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About

Long-Jye Sheu is a leading researcher in autonomous robotics, specializing in indoor mobile robot (IMR) navigation, simultaneous localization and mapping (SLAM), and intelligent motion control. His most impactful work introduces **Exploration-Based SLAM (e-SLAM)** , a novel framework that enables robots to autonomously explore unknown indoor environments using only a single LiDAR sensor. In his seminal 2022 paper (29 citations), Sheu demonstrates how an IMR can construct a complete map of an unexplored floor from scratch, solving the critical "kidnapped robot problem" without prior knowledge. His 2023 follow-up (14 citations) advances this by integrating path planning and motion control, generating traversable routes from simple floor plans and enabling smooth navigation through vertices. Sheu’s contributions are particularly notable for their sensor-minimal approach—achieving robust SLAM with limited hardware—making his work highly practical for cost-sensitive applications in warehouse logistics, service robotics, and disaster response. With over 40 combined citations for his e-SLAM series, Sheu has established a clear, scalable methodology that bridges exploration, mapping, and control, offering a foundational toolkit for researchers and engineers building next-generation autonomous indoor robots.