Yue-Yue Chen
Papers
2
Total Citations
11
H-Index
2
About
Yue-Yue Chen is a researcher specializing in intelligent robotics and autonomous navigation, with a particular focus on local path planning in static-obstacle environments. Her major contributions lie in the development of novel control strategies that integrate particle swarm optimization (PSO) with receding horizon control to address fundamental challenges in mobile robot motion. Chen’s most-cited work, "PSO-based receding horizon control of mobile robots for local path planning" (2017, 6 citations), introduces an innovative approach where a virtual robot is designed to navigate along obstacle boundaries, enabling effective collision avoidance within a predictive control framework. Her complementary study, "A method for solving local minimum problem of local path planning based on particle swarm optimization" (2017, 5 citations), further advances the field by tackling the persistent local minimum issue in path planning—a critical barrier to reliable autonomous navigation. By leveraging PSO to guide virtual robot movement along obstacle edges, Chen’s work provides computationally efficient solutions that enhance robot autonomy in cluttered environments. While her citation counts reflect a focused, emerging impact, these contributions represent meaningful steps toward more robust and intelligent robotic systems, offering practical methodologies for students and researchers working on mobile robot control and optimization-based navigation.
Research Focus
Key Achievements
Top Papers
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- 2