Punyavee Chaisiri
Papers
2
Total Citations
3
H-Index
1
About
Punyavee Chaisiri is a researcher advancing the field of autonomous mobile robotics, with a focus on precision navigation and energy efficiency in industrial cleanroom environments. Her work addresses critical challenges in hard disk drive production lines, where even minor localization errors can disrupt manufacturing. In her highly cited 2023 paper, she proposed a novel sensor fusion approach combining Light Detection and Ranging (LiDAR) with iBeacon technology to correct adaptive Monte Carlo localization (AMCL) errors caused by similar LiDAR data in different locations—enhancing robot accuracy and reliability. With 2 citations, this work demonstrates practical impact in high-stakes automation. Her second notable contribution applies recurrent neural networks to predict energy consumption of differential drive mobile robots, enabling smarter battery management and task queue optimization. By modeling power usage of individual components, her research helps reduce downtime and improve operational efficiency in cleanroom logistics. Chaisiri’s work sits at the intersection of sensor fusion, machine learning, and industrial robotics, offering tangible solutions for smart manufacturing. Her contributions are particularly valuable for students and engineers seeking to understand how AI and sensor integration can solve real-world localization and energy challenges in automated systems.
Research Focus
Key Achievements
Top Papers
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- 2