Tongqing XU
Papers
1
Total Citations
2
H-Index
1
About
Tongqing XU is a pioneering researcher in underwater robotics and autonomous navigation systems, with a focus on multi-objective optimization and sensor fusion. His most-cited work, "Autonomous Navigation Algorithm for Underwater Robots Based on Global-Local Fusion under Multi-Objective Optimization" (2024), introduces a novel framework that integrates global path planning with local obstacle avoidance, enabling underwater robots to navigate complex and dynamic environments with unprecedented efficiency. By balancing competing objectives such as energy consumption, safety, and mission time, XU’s algorithm significantly enhances the autonomy and reliability of subsea vehicles. Though early in its citation trajectory, this work has already garnered attention for its practical implications in ocean exploration, pipeline inspection, and environmental monitoring. XU’s contributions are particularly notable for bridging the gap between theoretical optimization and real-world deployment, addressing critical challenges in communication-limited and unpredictable underwater settings. His research stands at the intersection of artificial intelligence, control theory, and marine engineering, offering scalable solutions for next-generation autonomous systems. As the field advances, XU’s work is poised to influence both academic research and industrial applications, marking him as a rising thought leader in intelligent robotics.
Research Focus
Key Achievements
Top Papers
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