Kunxi Tang
Papers
4
Total Citations
19
H-Index
3
About
Kunxi Tang is a robotics researcher specializing in trajectory tracking control for mobile robots, with a focus on emergency response applications. His work centers on advancing model predictive control (MPC) through innovative integration of Koopman operator theory and event-triggered mechanisms, as demonstrated in his 2024 paper on emergency supplies transportation robots (7 citations). Tang’s major contributions include developing a dual closed-loop control structure combining Linear MPC with Adaptive Integral Sliding Mode Control (LMPC-AISMC) for nonholonomic wheeled mobile robots, enabling coordinated motion and force control while enhancing ground adaptation (6 citations). His 2025 work on deep Koopman operator modeling further extends these methods, improving trajectory accuracy through data-driven dynamics. With a growing citation record across his most-cited papers, Tang’s research directly addresses critical challenges in autonomous navigation for disaster relief, where precise trajectory tracking ensures timely delivery of emergency supplies. His achievements highlight a practical impact on robotics for humanitarian applications, making his work particularly relevant for students and researchers in control systems, autonomous vehicles, and rescue robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4