Papers
3
Total Citations
19
H-Index
3
About
Jiayuan Wang’s research focuses on intelligent robotics and multi-objective optimization, with a particular emphasis on improving the autonomy and precision of robotic systems. Wang’s major contributions lie in developing novel algorithms that address fundamental limitations in robot path planning and control. For instance, Wang proposed a multi-objective firefly algorithm enhanced with archive learning, which overcomes the common defects of slow convergence and low solution precision by preserving elite particles from each generation in an external archive. This work, published in 2019, has accumulated 9 citations, demonstrating its relevance to the field. Building on this foundation, Wang extended the approach to dynamic systems, introducing a multi-objective optimization-based path tracking method for two-wheeled self-balancing robots. By leveraging an artificial immune algorithm to optimize controller parameters, this 2023 study has already garnered 4 citations, highlighting its practical impact. Wang’s work is notable for bridging theoretical optimization techniques with real-world robotic applications, offering robust solutions for complex, multi-objective challenges in autonomous navigation and control.
Research Focus
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Top Papers
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