Papers
1
Total Citations
16
H-Index
1
About
Yisu Shi is a robotics researcher whose work focuses on advancing autonomous navigation through innovative path-planning algorithms. His primary research areas include mobile robotics, sensor fusion, and intelligent control systems, with a particular emphasis on improving the efficiency and adaptability of robotic movement in complex environments. Shi’s most notable contribution is his 2024 paper, "An Improved Global and Local Fusion Path-Planning Algorithm for Mobile Robots," which has already garnered 16 citations—a strong early impact for a recent publication. In this work, he addresses critical limitations in existing path-planning methods, such as path redundancy, excessive turning points, and poor environmental adaptability, by proposing a novel fusion algorithm that integrates global and local planning strategies. This approach enhances the robustness and smoothness of robot trajectories, making it highly relevant for real-world applications in logistics, exploration, and service robotics. Shi’s research demonstrates a clear commitment to solving practical challenges in autonomous systems, and his growing citation record signals his emerging influence in the field. For students and researchers interested in robotics and AI-driven navigation, Shi’s work offers valuable insights into the next generation of path-planning technologies.
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Top Papers
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