Jinqi Zhang
Papers
2
Total Citations
24
H-Index
2
About
Jinqi Zhang is a researcher whose work bridges the critical intersection of robotics, autonomous navigation, and intelligent control systems. Their primary research areas include autonomous navigation for agricultural robotics, adaptive control for flexible mechanical systems, and the application of neural networks to complex dynamic environments. Zhang’s most notable contribution is the development of an autonomous navigation method for orchard mobile robots that leverages octree-based 3D point cloud optimization. This work, which has already garnered 17 citations since its 2025 publication, addresses the fundamental challenge of balancing the rich environmental data from 3D LiDAR with the computational efficiency required for real-time operation in agricultural settings. Additionally, Zhang has made significant strides in the control of flexible marine riser systems, where they developed an adaptive neural network-based boundary control method capable of handling unknown nonlinear disturbances and output constraints. This work, cited 7 times, demonstrates Zhang’s ability to tackle complex distributed parameter systems with practical engineering constraints. Their research represents a meaningful contribution to both precision agriculture and offshore engineering, offering computationally efficient solutions to real-world control and navigation challenges.
Research Focus
Key Achievements
Top Papers
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