Jing Mu
Papers
1
Total Citations
2
H-Index
1
About
Jing Mu is a researcher focused on advancing the control and autonomy of mobile robotic systems, particularly in challenging agricultural and off-road environments. Her work addresses critical issues in trajectory tracking for tracked robots, where factors like uneven terrain, parameter uncertainty, and feedback integrity can severely degrade performance. Mu’s major contribution lies in developing an adaptive trajectory tracking sliding mode control method that robustly handles these uncertainties, ensuring precise and stable robot navigation even under unpredictable field conditions. This work, published in 2022, has garnered 2 citations, reflecting its relevance to the growing field of agricultural robotics. By tackling the practical challenges of real-world deployment—such as ground smoothness and external disturbances—Mu’s research bridges the gap between theoretical control systems and applied robotics. Her achievements are particularly notable for their potential to enhance the efficiency and reliability of autonomous agricultural vehicles, a key area in precision farming. For students and researchers in robotics and control engineering, Mu’s work offers a compelling example of how adaptive control strategies can solve complex, real-world problems in mobile robot navigation.
Research Focus
Key Achievements
Top Papers
- 1