Jianjun Bai
Papers
7
Total Citations
464
H-Index
5
About
Jianjun Bai is a control systems researcher whose work centers on autonomous mobile robotics, with a particular focus on trajectory tracking control for wheeled mobile robots (WMRs). His most influential contribution, a 2015 paper garnering nearly 400 citations, introduced a model predictive control (MPC) framework enhanced by neural-dynamic optimization, enabling robots to navigate reference trajectories while respecting real-world actuator constraints — a landmark advance in autonomous driving capabilities for robotic systems. Building on this foundation, Bai has systematically tackled some of the field's most persistent challenges: kinematic parameter uncertainty, input saturation, torque constraints, and wheel slippage phenomena including both longitudinal slipping and skidding. A recurring strength in his methodology is the development of generalized robot models that account for the displacement between a robot's center of mass and its wheel midpoint — a refinement that yields more physically accurate and robust controllers. His work employs rigorous Lyapunov-based stability analysis to guarantee global stability of proposed control laws. Across his publication record, Bai demonstrates a progressive and thorough research agenda, steadily expanding the operational envelope within which mobile robots can reliably and safely track trajectories in complex, constrained environments.
Research Focus
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Top Papers
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