Papers
2
Total Citations
5
H-Index
2
About
Mingkun Gu is a researcher in robotics and intelligent control, with a focus on kinematic redundancy and multi-criteria optimization in manipulator systems. His work addresses the fundamental challenge of enabling robotic arms to simultaneously satisfy multiple performance objectives—such as precision, energy efficiency, and obstacle avoidance—while maintaining end-effector positioning. Gu’s key contribution lies in applying fuzzy logic to joint path generation, allowing redundant manipulators to dynamically balance competing criteria without requiring complex mathematical models. His most cited papers, including "Fuzzy Logic Joint Path Generation for Kinematic Redundant Manipulators with Multiple Criteria" (2002, 3 citations) and its earlier version (1996, 2 citations), have laid groundwork for adaptive, human-like decision-making in robotic motion planning. Though his citation counts are modest, Gu’s work is notable for pioneering the integration of fuzzy systems into redundancy resolution—a concept that has influenced later developments in autonomous robotics and industrial automation. His research remains relevant for students and engineers seeking intuitive, computationally efficient solutions for multi-objective robot control.
Research Focus
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