Keyi Guo

Nanjing University of Science and Technology

Papers

Total Citations

H-Index

About

Keyi Guo is a researcher advancing the field of autonomous vehicle control, with a focus on unmanned driving robots and intelligent manipulation systems. Their work centers on developing robust control strategies that ensure precise and stable vehicle behavior under real-world uncertainties. In their highly cited 2022 paper (21 citations), Guo introduced a speed tracking method for unmanned driving robots that combines fuzzy adaptive systems with sliding mode control, enabling accurate speed regulation despite varying road conditions and disturbances. This contribution addresses a critical challenge in autonomous mobility: maintaining stable velocity profiles without human intervention. Another notable achievement, with 8 citations, is a neural active disturbance rejection adaptive lateral manipulation control method. This work integrates a steering manipulator model with the vehicle’s dynamics to achieve reliable path tracking and steering control, effectively handling external disturbances through adaptive neural compensation. Guo’s research bridges theoretical control engineering and practical robotics, offering solutions that enhance the safety and reliability of unmanned driving systems. Their contributions are valuable for students and engineers working on autonomous navigation, robotics, and intelligent transportation, demonstrating how adaptive and neural control methods can solve complex real-world driving challenges.