Papers
1
Total Citations
5
H-Index
1
About
Yucong Su is a researcher focused on intelligent robotics and autonomous navigation, with a particular emphasis on path planning for inspection robots in complex industrial environments. His most-cited work, "Global path planning for airport energy station inspection robots based on improved grey wolf optimization algorithm" (2023, 5 citations), addresses a critical challenge in autonomous robotics: navigating through confined, equipment-dense spaces typical of airport energy stations. Su’s major contribution lies in enhancing the grey wolf optimization algorithm to overcome the limitations of traditional path planning methods, enabling robots to efficiently find optimal routes in narrow, obstacle-rich areas. This work has practical implications for improving the safety and efficiency of infrastructure inspections. While his citation count is still growing, Su’s research demonstrates a strong foundation in applying nature-inspired algorithms to real-world robotic systems. His achievements highlight a promising trajectory in the field of intelligent robotics, particularly for industrial automation and smart infrastructure maintenance.
Research Focus
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Top Papers
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