Endah Kinarya Palupi

Sunan Gunung Djati State Islamic University Bandung, Kwansei Gakuin University

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About

Endah Kinarya Palupi is a researcher specializing in robotics, automation, and intelligent control systems, with a particular focus on applying machine learning techniques to robotic manipulation and motion planning. Her work sits at the intersection of embedded systems, computer vision, and artificial intelligence, addressing real-world industrial challenges through innovative engineering solutions. Palupi's most recognized contribution is her 2018 study on colored object sorting using a 5-degrees-of-freedom (DoF) robot arm driven by an Artificial Neural Network (ANN), which has garnered 11 citations. This work demonstrated a practical, Arduino-based system capable of real-time object recognition and sorting — a significant step toward accessible, intelligent automation in industrial settings. Building on this foundation, her 2021 research explored inverse kinematics modeling combined with an Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict and control robotic arm motion angles with greater precision, reflecting her ongoing commitment to advancing smart robotic control strategies. Together, her publications highlight a consistent research trajectory aimed at making robotic systems more adaptive, accurate, and practically deployable. For students and researchers working in robotics or industrial automation, Palupi's contributions offer valuable insights into integrating AI-driven methods with hardware systems to solve tangible engineering problems.