Papers
3
Total Citations
16
H-Index
2
About
Yujing Long is a researcher specializing in robotics path planning, autonomous navigation, and military robotics applications. Their most significant contribution is the development of a hybrid path planning method for autonomous patrol robots, combining a modified A* algorithm with a genetic algorithm to search for the shortest patrol path. This work, published in 2022 and garnering 12 citations, also introduced a simplified coordinate transformation method to convert GPS coordinates into grid coordinates for efficient robot movement. Long further advanced this line of research by integrating A* and ant colony algorithms to improve patrol efficiency and reduce computation time. In the domain of defense technology, Long explored the integration of robotics into future intelligent soldier squads, examining how robots and Individual Combat Systems (ICS) could transform traditional combat concepts. With a total of 16 citations across their most-cited works, Long’s research contributes practical algorithms for autonomous navigation and offers strategic insights into the role of robotics in modern military operations.
Research Focus
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Top Papers
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