Shiping Zhang
Papers
1
Total Citations
2
H-Index
1
About
Shiping Zhang is a robotics researcher specializing in intelligent control systems for autonomous mobile platforms. Their work focuses on advancing trajectory tracking for non-holonomic wheeled mobile robots (NWMRs), addressing critical limitations in traditional PID control such as poor accuracy, high response delays, and insufficient robustness. Zhang’s most cited paper, "Research on trajectory tracking of wheeled mobile robots using fuzzy PID based on TD3" (2024, 2 citations), introduces a novel hybrid control strategy that integrates Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning with fuzzy PID logic. This approach significantly improves real-time adaptability and stability in complex environments, marking a notable contribution to the intersection of deep reinforcement learning and classical control theory. By bridging the gap between model-free learning and traditional control, Zhang’s work offers practical solutions for autonomous navigation in industrial and service robotics. Their research is particularly valuable for students and engineers seeking to enhance mobile robot performance through intelligent, data-driven control methodologies.
Research Focus
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Top Papers
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