Zhengtian Wu
Papers
15
Total Citations
353
H-Index
8
About
Zhengtian Wu is a prolific robotics and control systems researcher whose work spans autonomous navigation, intelligent motion planning, and advanced control theory. Best known for his pioneering contributions to robot path planning, Wu has developed innovative algorithms that address one of the field's most persistent challenges: escaping local minima in complex environments. His highly cited work on simulated annealing-based path planning and artificial potential field methods—together accumulating over 230 citations in 2023 alone—has established him as a leading voice in mobile robotics navigation. Beyond path planning, Wu has made notable contributions to sliding-mode control theory, Markovian jump systems, and neural network-based state estimation, reflecting a broad command of nonlinear and stochastic control frameworks. His research extends into emerging applications including multi-robot coordination, industrial IoT scheduling, and the optical manipulation of biological cells using stochastic control approaches—demonstrating impressive interdisciplinary range. Wu's exploration of bio-inspired artificial muscles further underscores his interest in next-generation actuator technologies. With a rapidly growing citation profile across multiple domains, Wu represents a dynamic and versatile researcher whose work bridges theoretical control systems and real-world robotics applications.
Research Focus
Key Achievements
Top Papers
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- 6Multi-robot dynamic path planning with priority based on simulated annealing11 citations · 2024
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