Xiangrui Ran

Papers

Total Citations

119

H-Index

About

Xiangrui Ran is a leading researcher in autonomous underwater vehicle (AUV) technology, specializing in fault diagnosis, path planning, and safe navigation in complex marine environments. Their most influential work, "Thruster fault diagnosis method based on Gaussian particle filter for autonomous underwater vehicles" (2016, 78 citations), introduced a novel approach to detecting actuator failures—a critical challenge given that AUVs operate in remote, hazardous conditions where system reliability is paramount. This method enhances automatic fault diagnosis, reducing the risk of costly mission failures. Ran further advanced the field with "A 2D Optimal Path Planning Algorithm for Autonomous Underwater Vehicle Driving in Unknown Underwater Canyons" (2021, 41 citations), addressing the safe navigation of AUVs through treacherous deep-sea terrains like underwater canyons and mountains. By developing algorithms that enable real-time, collision-free path planning in unknown environments, Ran’s work directly supports the deployment of AUVs for ocean exploration, surveillance, and resource management. With over 119 citations across their top papers, Ran’s contributions are foundational to improving AUV autonomy and operational safety, making them a key figure in marine robotics research.