Iswanto Suwarno
Papers
8
Total Citations
69
H-Index
4
About
Iswanto Suwarno is a prolific robotics and control systems researcher whose work spans intelligent automation, autonomous navigation, and healthcare robotics. His research is distinguished by the creative fusion of advanced control methodologies — including fractional-order controllers, ANFIS-based systems, and optimization algorithms — with real-world robotic applications. His most-cited work, garnering 28 citations, investigates the optimization of Robotic Arm-Based Conveyor Belt motions using a sophisticated NARMA(L2)-FO(ANFIS)PD-I framework combined with Jaya Optimization, demonstrating his command of cutting-edge industrial automation. Suwarno has also made meaningful contributions to mobile robotics, developing stereo vision-based obstacle avoidance systems (15 citations) and IoT-enabled telepresence robots using PID control and Kalman filtering (10 citations) — the latter directly addressing challenges faced by medical personnel during the COVID-19 pandemic. His socially conscious research extends to UV sterilization robots and aromatherapy robots deployed within mosque communities during the pandemic. More recently, his exploration of MobileNetV2 SSD-based ball detection for autonomous soccer robots reflects a growing engagement with deep learning in robotics. Collectively accumulating over 60 citations, Suwarno's body of work reflects a researcher committed to translating intelligent control theory into impactful, human-centered robotic solutions.
Research Focus
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