Shouren Zhong
Papers
2
Total Citations
16
H-Index
2
About
Shouren Zhong is a leading researcher in autonomous vehicle motion control and localization, whose work addresses critical challenges in intelligent transportation systems. His primary research areas include model predictive control (MPC) for autonomous driving and visual-inertial odometry (VIO) for vehicle localization. Zhong’s major contribution lies in developing offset-free MPC methods that solve the steady-state error problem caused by parameter perturbations in dynamic driving environments—a key barrier to reliable autonomous vehicle control. His 2022 paper on this topic has garnered 10 citations, reflecting its practical significance. Additionally, Zhong advanced vehicle localization with his consistent monocular Ackermann VIO approach, which improves scale observability during degenerate motions by fusing Ackermann kinematic constraints. This 2020 work, with 6 citations, addresses the critical issue of maintaining localization accuracy when vehicles move in constrained patterns. By tackling both control precision and localization robustness, Zhong’s research bridges fundamental gaps in autonomous vehicle technology, offering solutions that enhance safety and reliability in real-world driving scenarios. His work continues to influence the development of intelligent and connected vehicle systems.
Research Focus
Key Achievements
Top Papers
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