Indrazno Siradjuddin
Papers
24
Total Citations
243
H-Index
7
About
Indrazno Siradjuddin is a robotics and control systems researcher whose work spans visual servoing, robot manipulator control, and mobile robotics. He is best known for his pioneering contributions to image-based visual servoing (IBVS), particularly his development of adaptive distributed fuzzy PD controllers for redundant robot manipulators. His most influential paper, published in 2014 and garnering 91 citations, introduced a Takagi-Sugeno fuzzy framework for controlling 7-DOF robot manipulators through visual feedback — a significant advancement over conventional machine learning approaches. Building on earlier foundational work from 2010, Siradjuddin systematically refined intelligent control architectures for vision-guided robotic systems. His 2012 contribution leveraging Microsoft's Kinect camera for position-based visual tracking demonstrated a practical, cost-effective approach to 3D robotic guidance. Beyond manipulators, his research extends to mobile robotics, including self-balancing robots, omnidirectional wheeled vehicles, autonomous guided vehicles, and immersive teleoperation systems utilizing 360-degree cameras and VR headsets. With over 200 cumulative citations, Siradjuddin has established himself as a productive contributor to applied robotics, consistently bridging theoretical control design with accessible, real-world implementation — making his work particularly valuable to engineers and researchers developing intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6A low cost 3D-printed robot joint torque sensor10 citations · 2018
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