Papers
1
Total Citations
10
H-Index
1
About
Wu Chen is a researcher specializing in robotics, optimization algorithms, and intelligent manufacturing systems. His work focuses on the development and application of hybrid metaheuristic algorithms to solve complex real-world engineering problems, particularly in the domain of industrial automation and welding robotics. His most notable contribution is the 2019 paper on a Hybrid Global Optimum Beetle Antennae Search–Genetic Algorithm (BAS-GA) for welding robot path planning, which has garnered 10 citations and demonstrates his innovative approach to combining nature-inspired optimization techniques. In this work, Chen addressed the challenging problem of coordinating body-in-white spot welding robots by integrating the Beetle Antennae Search algorithm with Genetic Algorithm iterations, achieving meaningful improvements in welding efficiency and path optimization. This contribution reflects his broader commitment to bridging theoretical algorithmic research with practical industrial applications, particularly in smart manufacturing environments. Chen's research is relevant to engineers and computer scientists alike, offering scalable solutions to multi-constraint optimization problems in robotic systems. His work represents a growing body of scholarship that leverages bio-inspired computation to advance the capabilities of modern automated production lines.
Research Focus
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Top Papers
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