Papers
1
Total Citations
11
H-Index
1
About
Xiang Ai is a researcher specializing in adaptive control, multi-agent systems, and fault-tolerant formation tracking, with a focus on networked mobile robots. Their most-cited work, "Adaptive fault-tolerant formation tracking control of networked mobile robots with input delays" (2023, 11 citations), addresses critical challenges in coordinating robot teams under real-world constraints like communication delays and actuator faults. This contribution is pivotal for advancing autonomous systems in applications such as search-and-rescue, warehouse logistics, and environmental monitoring, where reliability and precision are paramount. By developing adaptive algorithms that maintain formation stability despite input delays, Ai’s research bridges theoretical control theory and practical robotics, offering robust solutions for dynamic, uncertain environments. Their work has garnered attention for its potential to enhance safety and efficiency in multi-robot operations, laying groundwork for future studies in resilient networked systems. Ai’s achievements underscore a commitment to solving pressing problems in automation and cyber-physical systems, making their research a valuable resource for students and engineers exploring fault-tolerant control and cooperative robotics.
Research Focus
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Top Papers
- 1