Mingzhu Wei

Politecnico di Torino, University of Electronic Science and Technology of China

Papers

Total Citations

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About

Mingzhu Wei is a leading researcher in multi-agent coordination and autonomous robotics, with a focus on distributed localization, collaborative search, and coverage optimization. Her most influential work, "A Distributed Technique for Localization of Agent Formations From Relative Range Measurements" (2012, 43 citations), addresses a critical challenge in large-scale autonomous systems: enabling agents to determine their positions without relying on absolute sensors like GPS. By developing a scalable, relative-range-based approach, Wei’s method allows formations of unmanned vehicles—whether ground-based or aerial—to maintain spatial awareness through local interactions, a foundational contribution to swarm robotics. She further advances the field with her 2019 study on multi-UAV collaborative searching in 3D space, which integrates an `8'-shape trajectory model with genetic algorithms to minimize target search time. Her 2020 work on coverage optimization using virtual force refinement enhances multi-robot exploration for applications like disaster detection, while her 2019 planetary rover path planning study improves autonomous navigation on extraterrestrial terrains. With over 59 citations across her key papers, Wei’s research has practical implications for defense, space exploration, and environmental monitoring, establishing her as a pivotal figure in distributed autonomous systems.