Yuxiang Chen

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About

Yuxiang Chen is a researcher specializing in underwater robotics and autonomous navigation systems, with a particular focus on real-time obstacle avoidance for subsea environments. Their most cited work, "The underwater obstacle avoidance method based on ROS" (2023), addresses a critical challenge in marine robotics: enabling autonomous underwater vehicles to navigate safely and efficiently in dynamic, unstructured environments. By applying the artificial potential field method within the Robot Operating System (ROS) framework, Chen's research mitigates the problem of excessive attractive forces when robots are far from their target, improving path planning reliability. Though early in their citation impact—with 2 citations to date—this work represents a foundational contribution to practical, ROS-integrated solutions for underwater navigation. Chen's research bridges theoretical control algorithms with real-world robotic applications, offering scalable approaches for marine exploration, environmental monitoring, and offshore infrastructure inspection. Their contributions are particularly relevant for students and engineers seeking to implement robust, low-cost obstacle avoidance systems in underwater platforms, highlighting the growing importance of open-source software in advancing autonomous marine technologies.