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About

Xiaomei Liu is a robotics and control systems researcher whose work spans multi-agent systems, human-robot interaction, and intelligent control theory. Her research has made significant contributions to the design and analysis of multi-agent coordination, particularly in formation control and adaptive tracking under real-world constraints. Liu's most influential work, "Vision-Based Leader–Follower Formation Control of Multiagents With Visibility Constraints" (2018, 74 citations), demonstrated an innovative approach to multi-agent formation control using only Kinect sensors—eliminating the need for inter-agent communication. This breakthrough has shaped how researchers think about practical, low-cost deployment of autonomous robot teams. Her subsequent work on event-triggered adaptive bipartite finite-time tracking control (2023, 55 citations) advanced the field further by addressing complex coopetition dynamics in nonlinear multi-agent systems under disturbances. Beyond theoretical control design, Liu has explored the human side of robotics, contributing to intelligent speech-based human-robot interaction and the mechanical design of service robots. This breadth reflects her commitment to bridging rigorous mathematical control frameworks with practical robotic applications. With nearly 150 citations across her career, Liu stands as a meaningful contributor to the evolving landscape of intelligent autonomous systems research.