Papers
51
Total Citations
1,521
H-Index
22
About
Ming Cao is a prolific researcher whose work spans multi-agent systems, formation control, robot navigation, and bioinspired sensing — fields that sit at the intersection of control theory, robotics, and networked dynamical systems. His foundational contributions to networked controllability, particularly his 2012 study on single-leader consensus networks (181 citations), established key insights into how network topology governs a system's manageability — work with profound implications for distributed robotics and sensor networks. Cao has significantly advanced rigid formation control, demonstrating how mobile agents can achieve and maintain precise geometric configurations even under measurement inconsistencies, with his 2016 paper on rotational and translational maneuvering accumulating 147 citations. His development of angle rigidity theory (112 citations) opened new possibilities for formations relying solely on angular measurements. Beyond classical control, Cao has pioneered singularity-free path-following algorithms for robot navigation and explored large language models for autonomous visual navigation. Remarkably, his research also extends into bioinspired sensing, with award-worthy investigations into seal whisker hydrodynamics and 3D-printed graphene MEMS sensors that replicate nature's ultrasensitive flow detection. Collectively, his work has garnered hundreds of citations, reflecting sustained, cross-disciplinary influence on modern autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3Angle Rigidity and Its Usage to Stabilize Multiagent Formations in 2-D112 citations · 2020
- 4Singularity-Free Guiding Vector Field for Robot Navigation94 citations · 2021
- 5L3MVN: Leveraging Large Language Models for Visual Target Navigation81 citations · 2023
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- 10Adaptive leader-follower formation control for autonomous mobile robots47 citations · 2010