Mingli Wang
Papers
7
Total Citations
130
H-Index
6
About
Mingli Wang is a leading researcher in advanced robotics, specializing in trajectory generation, feedrate scheduling, and dynamic control for hybrid and industrial robot systems. Their work addresses critical challenges in high-speed, high-precision robotic operations, particularly for complex tasks like 5-DOF hybrid robot motion and dual-robot mirror milling of thin-walled workpieces. Wang’s major contributions include developing a jerk-limited heuristic feedrate scheduling method using particle swarm optimization (48 citations), which ensures smooth motion under kinematic and dynamic constraints, and a third-order constrained time-optimal feedrate planning algorithm (14 citations) for smooth, bounded-velocity trajectories. They also pioneered a constant plunge depth control strategy for robotic friction stir welding (17 citations) and a real-time trajectory generator with third-order constraint satisfaction (4 citations), enabling rapid, smooth response to external commands. With over 130 total citations, Wang’s work has significantly advanced the precision and efficiency of robotic manufacturing, particularly in aerospace and automotive applications. Their research is essential for students and engineers seeking to optimize robot motion planning and control in high-stakes industrial environments.
Research Focus
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