Zhongke Gao
Papers
1
Total Citations
8
H-Index
1
About
Zhongke Gao is a researcher whose work lies at the intersection of autonomous navigation, computational geometry, and marine robotics. His most cited contribution, "AD-RRT*: An RRT*-based global path planning approach for underwater gliders with alpha shapes and DBSCAN" (2025), introduces a novel path planning algorithm that enhances the efficiency and safety of autonomous underwater vehicles. By integrating alpha shapes for obstacle representation and DBSCAN clustering for environmental analysis, Gao’s method significantly improves the adaptability of RRT*-based planning in complex, dynamic underwater terrains. This work has already garnered 8 citations, reflecting its immediate relevance to the field. Gao’s research addresses critical challenges in marine exploration, including collision avoidance and energy-efficient route generation, with potential applications in oceanographic monitoring and underwater search missions. His approach stands out for its computational robustness and practical deployability, marking him as an emerging contributor to intelligent robotics. For students and researchers in autonomous systems, Gao’s work offers a compelling example of how geometric and clustering techniques can be harnessed to solve real-world navigation problems.
Research Focus
Key Achievements
Top Papers
- 1