Papers
1
Total Citations
3
H-Index
1
About
Xuyang Wu is a researcher focused on autonomous navigation and path planning for unmanned ground vehicles (UGVs), particularly in complex, unstructured environments. His most cited work, "Unmanned Ground Vehicle in Unstructured Environments Applying Improved A-star Algorithm" (2024, 3 citations), addresses a critical challenge in robotics: enabling UGVs to navigate safely and efficiently where traditional path planning fails. Wu’s major contribution lies in enhancing the classic A-star algorithm to account for the kinematic constraints of UGVs—specifically longitudinal motion—while optimizing for both path length and computational efficiency. This work has practical implications for autonomous agriculture, disaster response, and military logistics. Though early in his career, Wu’s research has already garnered attention for its pragmatic approach to real-world robotics problems. His focus on bridging algorithmic theory with vehicle dynamics positions him as an emerging voice in field robotics, with potential for significant impact as autonomous ground vehicles become more prevalent in off-road and industrial applications.
Research Focus
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Top Papers
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