Yukun Hu

Papers

Total Citations

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About

Yukun Hu is a prominent researcher in autonomous underwater vehicle (AUV) navigation and path planning, with a focus on developing efficient, real-time algorithms for complex underwater environments. Their most cited work, the 2017 paper on “Path optimization of AUV based on smooth-RRT algorithm” (33 citations), introduces a novel routing optimization method that enhances the Rapidly-exploring Random Tree (RRT) algorithm by incorporating convergence and angle factors. This innovation significantly improves path smoothness and computational efficiency, addressing critical challenges in AUV operations such as obstacle avoidance and real-time decision-making. Hu’s contributions have advanced the field of marine robotics, providing practical solutions for autonomous systems operating in dynamic, unstructured settings. With a growing citation impact, their research continues to influence both academic studies and applied engineering in underwater exploration and defense. Hu’s work exemplifies the integration of algorithmic theory with real-world robotic applications, making them a key figure in the development of smarter, more reliable autonomous vehicles.