Katherin Indriawati
Papers
1
Total Citations
2
H-Index
1
About
Dr. Katherin Indriawati is a leading researcher in industrial automation and intelligent manufacturing systems, with a primary focus on optimizing material flow through advanced robotics and machine learning. Her work centers on developing adaptive control strategies for automated guided vehicles (AGVs) and cellular conveyors, addressing critical challenges in flexible manufacturing environments. Her most cited paper, "Path Planning for 4-Wheeled Omnidirectional Cellular Conveyor using Q-Learning Algorithm" (2024), introduces a novel reinforcement learning approach to enable dynamic, decentralized path planning for modular conveyor systems—a significant departure from traditional fixed-belt conveyors. This work has already garnered early citations, reflecting its potential to transform production line efficiency. Dr. Indriawati’s contributions bridge the gap between theoretical AI algorithms and practical industrial applications, offering scalable solutions for smart factories. Her research is particularly notable for integrating Q-learning with omnidirectional mobility, allowing conveyors to adapt in real-time to changing layouts and object destinations. By pioneering these intelligent material handling systems, she is helping to define the next generation of adaptive, autonomous manufacturing infrastructure.
Research Focus
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Top Papers
- 1