Wanting Zeng
Papers
2
Total Citations
73
H-Index
2
About
Wanting Zeng is a robotics researcher whose work centers on autonomous mobile robot navigation, fuzzy logic control, and multi-robot cooperation in complex environments. Her research addresses one of the fundamental challenges in robotics: enabling robots to intelligently navigate unknown, obstacle-laden environments while performing collaborative tasks. Zeng's most influential contribution, "Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments" (2014), has garnered 70 citations and demonstrates her expertise in combining evolutionary computation with fuzzy control systems. This work introduced a leader-follower framework in which two wheeled mobile robots coordinate to perform obstacle boundary following and target seeking behaviors, enabling them to transport objects through uncharted terrain — a significant advance for practical robotic deployment. Building on this foundation, her 2016 paper extended the navigation framework to address concave map environments and the challenging dead-cycle problem, refining multi-robot cooperation strategies with enhanced behavioral repertoires including cooperative target searching. Zeng's research has meaningful implications for warehouse automation, search-and-rescue operations, and assistive robotics. Her integration of evolutionary optimization with fuzzy control provides robust, adaptable solutions for real-world robotic systems operating under uncertainty.
Research Focus
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Top Papers
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