Erwin Susanto
Papers
9
Total Citations
54
H-Index
3
About
Erwin Susanto is a robotics and control systems researcher whose work spans manipulator arms, mobile robots, autonomous underwater vehicles, and intelligent control methodologies. His research is particularly distinguished by its practical focus on making complex robotic systems accessible through computationally efficient control strategies, including Proportional Derivative (PD) control, Fuzzy Logic, and increasingly, neural network approaches. Susanto's most cited contribution — a 2013 paper on PD-controlled robot arms using Microsoft Kinect (26 citations) — demonstrated how consumer-grade sensing technology could be leveraged for intuitive manipulator control, reducing reliance on complex mathematical computation. His subsequent work extended these principles to self-balancing two-wheeled robots, submarine robots, and food-delivery service robots, reflecting a broad commitment to real-world robotic applications. His 2022 work on rotary inverted pendulum stabilization combining PD and Fuzzy Logic controllers highlights his ongoing refinement of hybrid control strategies, while a 2024 neural network paper signals his engagement with modern machine learning techniques for 3DOF arm dynamics. With over 50 cumulative citations across diverse robotic platforms, Susanto's portfolio reflects a researcher steadily building a cohesive body of work at the intersection of embedded systems, control engineering, and practical robotics — making him a relevant reference point for students exploring intelligent control and microcontroller-based robotic design.
Research Focus
Key Achievements
Top Papers
- 1
- 2Implementasi Robot Keseimbangan Beroda Dua Berbasis Mikrokontroler10 citations · 2015
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- 5Neural Network Control for Dynamics of a 3DOF Robot Arm2 citations · 2024
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- 8RANCANG BANGUN KESTABILAN LAJU ROBOT KAPAL SELAM BERBASIS MIKROKONTROLER2 citations · 2016
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