Papers
7
Total Citations
240
H-Index
5
About
Zhenzhong Chu is a leading researcher in autonomous underwater vehicle (AUV) navigation and control, with a focus on adaptive sliding mode control and neural network-based systems. His most cited work, "Adaptive sliding mode control based on local recurrent neural networks for underwater robot" (2012, 121 citations), introduced a robust control method that significantly improves AUV stability in dynamic underwater environments. Chu also advanced path planning with his 2015 paper on artificial potential fields and velocity synthesis (59 citations), which uniquely accounts for ocean currents—a critical factor distinguishing underwater navigation from ground robotics. His recent 2023 study on distributed adaptive formation reconfiguration control for multiple AUVs in 3D ocean environments (36 citations) addresses complex multi-vehicle coordination, offering novel solutions for nonplanar formations. Beyond AUVs, Chu has explored combinatorial optimization with neural networks for the traveling salesman problem (2017) and biologically inspired intelligence for robot navigation (2018). With over 240 total citations, his work bridges theoretical control methods and practical underwater robotics, making him a key figure in advancing autonomous marine systems.
Research Focus
Key Achievements
Top Papers
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- 5Biologically Inspired Intelligence with Applications on Robot Navigation6 citations · 2018
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- 7Design of indoor mobile robot based on ROS and lidar3 citations · 2022