Papers
6
Total Citations
56
H-Index
4
About
Linying Xiang is a robotics and control systems researcher whose work centers on multi-robot coordination, distributed control, and autonomous path planning. Her research addresses some of the most practically significant challenges in modern robotics: enabling teams of robots to move intelligently, communicate efficiently, and adapt to dynamic environments. Xiang's foundational contributions lie in distributed control for nonholonomic mobile robots — systems with inherent movement constraints common in real-world platforms. Her early work (2014) introduced adaptive distributed control laws allowing robots to form precise geometric patterns while tracking reference trajectories with limited information, earning 10 citations. She subsequently pioneered event-triggered and self-triggered control frameworks (2015–2016), reducing unnecessary communication overhead while preserving formation integrity, with her 2016 paper accumulating 14 citations. Her more recent research expands into path planning and source localization. The 2021 NPQ-RRT* algorithm, her most cited work with 18 citations, proposes a hybrid planning approach improving upon the classical RRT* framework for multi-robot formation scenarios. Her 2023 work on simultaneous source localization and formation introduces a noise-robust, communication-efficient gradient-free algorithm, reflecting her growing focus on real-world deployment challenges. Collectively, Xiang's contributions advance the theoretical and practical foundations of intelligent, coordinated robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6