Papers

2

Total Citations

44

H-Index

2

About

Xiao Min is a leading researcher in the control of multi-agent robotic systems, with a primary focus on nonholonomic mobile robots and formation control. Her work addresses critical challenges in ensuring that teams of robots—such as leader–follower pairs—can maintain safe, constrained formations while operating under real-world limitations like limited communication range and performance constraints. In her highly cited 2023 paper (41 citations), she introduced a funnel-based asymptotic control method that guarantees formation constraints are strictly satisfied without violating connectivity or feasibility. This work is complemented by her 2022 study on low-complexity control, which tackles the practical need for computationally lightweight algorithms suitable for small robots with limited hardware. By avoiding complex function approximation and dynamic adaptive laws, her approach makes advanced formation control accessible for resource-constrained platforms. Xiao Min’s contributions are pivotal for the deployment of reliable, scalable multi-robot systems in applications such as search-and-rescue, environmental monitoring, and autonomous logistics, where both precision and simplicity are essential.

Research Focus

Key Achievements

2
H-Index
2
Papers
44
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Funnel-Based Asymptotic Control of Leader–Follower Nonholonomic Robots Subject to Formation Constraints
41 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Purple Mountain Laboratories, Southeast University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago