Yuan-Ting Fu
Papers
2
Total Citations
5
H-Index
2
About
Yuan-Ting Fu is a researcher specializing in autonomous navigation and path planning for robotic systems, with a particular focus on enabling safe and efficient movement in complex environments. Their work addresses critical challenges in smart factory automation and unmanned vehicle operations, where robots must navigate from start to destination while reliably avoiding obstacles. Fu’s key contributions include the development of a path planning algorithm using hierarchical four-parameter logistic curves, which ensures continuous-curvature avoidance for smoother, more realistic robot trajectories. Additionally, they introduced a Leading Rapidly-exploring Random Trees (RRT) algorithm, enhancing the efficiency of path generation in dynamic settings. With foundational research spanning mapping, localization, and navigation, Fu’s work has laid important groundwork for practical applications such as factory unmanned vehicles and delivery systems. Though early in their career, their papers have already attracted citations from peers working on similar robotics challenges, signaling growing influence in the field. Fu’s research continues to push toward more intelligent, autonomous systems that can operate reliably in real-world environments.
Research Focus
Key Achievements
Top Papers
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- 2