Papers
7
Total Citations
48
H-Index
5
About
Lan Anh Trinh is a robotics researcher whose work centers on the critical challenge of dependable multi-robot navigation in shared human environments. Her primary research areas include path planning, collision avoidance, and localization for autonomous systems. Trinh’s major contributions lie in developing novel frameworks that combine Petri net modeling with dipole flow fields and dynamic window approaches to prevent congestion and ensure safe, collision-free movement among multiple robots and humans. Her most cited paper, “Petri Net Based Navigation Planning with Dipole Field and Dynamic Window Approach for Collision Avoidance” (2019), along with closely related works from 2020 and 2022, each garnering 8–9 citations, collectively establish a robust methodology for dependable multi-agent path planning. Earlier in her career, Trinh also made notable contributions to robot localization, applying matrix pencil algorithms and hybrid DOA/TOA estimation (2012, 8 citations) to improve positioning accuracy. Her research is particularly significant for advancing the safe integration of autonomous robots into dynamic, human-populated workspaces, addressing a key bottleneck in modern robotics and automation.
Research Focus
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