Tingping Feng
Papers
5
Total Citations
59
H-Index
5
About
Tingping Feng is a rising leader in autonomous robotics, specializing in path planning, multi-robot coordination, and industrial servo control. Feng’s most impactful work introduces the Hybrid Adaptive Genetic Algorithm (HAGA), a breakthrough that enables mobile robots to dynamically adjust their routes based on task hazard levels and complex road environments—a paper that has already garnered 22 citations since 2024. For multi-robot systems, Feng developed a dual-layer symmetric path planning system integrating an improved neural network with the DWA algorithm, solving coordination challenges in dynamic settings (14 citations). In industrial robotics, Feng proposed a Hybrid Sparrow Search Algorithm (HSSA) for PID optimization, stabilizing servo systems against joint friction and load variations (12 citations). Additional contributions include dual-layer fuzzy control for diverse task safety, and a high-precision localization method fusing improved AMCL with QR code assistance for transport robots. Feng’s work bridges theoretical optimization with practical deployment, earning rapid recognition for solving real-world robotics challenges.
Research Focus
Key Achievements
Top Papers
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