Papers
3
Total Citations
56
H-Index
3
About
Honggang Wu is a rising researcher in the fields of robotics, optimization algorithms, and intelligent control systems. His work focuses on solving complex robotic challenges through bio-inspired meta-heuristic algorithms and advanced control strategies. Wu’s most notable contribution is the development of the Wild Geese Migration Optimization (GMO) algorithm, a novel meta-heuristic inspired by the social swarming behavior of wild geese. This algorithm, detailed in his most-cited paper (37 citations), has been successfully applied to solve the inverse kinematics of robots. He further advanced optimization techniques by proposing a hybrid improved Battle Royale Optimization (BRO) algorithm, integrating the level mechanism of Chicken Swarm Optimization to enhance computational performance for 7R 6DOF robot kinematics. In control systems, Wu introduced a parallel network-based sliding mode tracking control method for robotic manipulators with uncertain dynamics, achieving robust compensation for model uncertainties and external perturbations. His work bridges theoretical algorithm development with practical robotic applications, demonstrating significant impact in both optimization and control engineering.
Research Focus
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