Khattiya Pongsirijinda
Papers
4
Total Citations
29
H-Index
4
About
Khattiya Pongsirijinda is a robotics researcher whose work focuses on autonomous navigation, multi-robot coordination, and sensor fusion for localization in complex, real-world environments. Their major contributions lie in addressing two critical challenges: enabling accurate object localization under non-line-of-sight (NLOS) conditions, and developing communication-constrained exploration strategies for multi-robot teams. In their highly cited 2025 paper, Pongsirijinda pioneered a neural network approach to mitigate and compensate for NLOS ranging errors in Ultra-WideBand (UWB) systems, achieving robust localization where traditional methods fail. This work, alongside their fusion of UWB and LiDAR for moving object localization with mobile robots, has garnered significant attention (over 10 citations). Their 2024 and 2025 papers on multi-robot exploration—introducing distributed potential-field-based exploration with noise-augmented strategies and the MEF-Explore framework for communication-limited scenarios—demonstrate a deep understanding of practical deployment constraints. With a growing citation record and a clear trajectory toward solving fundamental problems in field robotics, Pongsirijinda is establishing themselves as a key contributor to the next generation of autonomous systems that must operate reliably under uncertainty and limited communication.
Research Focus
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Top Papers
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