Hugo Adeodatus Hendarto

Papers

Total Citations

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About

Hugo Adeodatus Hendarto is a robotics researcher whose work bridges computational intelligence and mechanical systems, with a particular focus on solving complex kinematic problems in industrial robotics. His most cited work, "ANFIS application for calculating inverse kinematics of programmable universal machine for assembly (PUMA) robot" (2014, 9 citations), demonstrates his innovative approach to a fundamental challenge in robotics: determining the joint angles required to achieve a desired end-effector position. By applying Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to the inverse kinematics problem—traditionally solved through computationally intensive geometric or algebraic methods—Hendarto introduced a more efficient, intelligent solution that leverages the Denavit-Hartenberg parameter method for forward kinematics. This work showcases his ability to combine classical robotics theory with modern machine learning techniques, offering practical improvements for robot control in assembly applications. While his citation count reflects a focused research trajectory, his contribution is significant for demonstrating how fuzzy neural networks can streamline real-time robot arm calculations, making his research valuable for engineers and students working on robotic manipulation and automation systems.