Dinita Rahmalia

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About

Dinita Rahmalia is an Indonesian researcher specializing in state estimation, robotics, and biomedical signal processing, with a particular focus on advanced Kalman filtering techniques applied to real-world engineering challenges. Her work spans autonomous systems, underwater robotics, and rehabilitation technology, reflecting a broad yet cohesive research vision centered on precise motion estimation in complex environments. Among her notable contributions, Rahmalia has explored the Square Root Unscented Kalman Filter (AK-UKF) for mobile robot position estimation, addressing critical challenges in GPS-dependent navigation systems. Her 2022 work on Ensemble Kalman Filter-based finger motion estimation for post-stroke rehabilitation demonstrates her commitment to socially impactful research, offering promising tools for patient recovery monitoring. More recently, she extended her expertise to maritime applications, developing Unscented Kalman Filter methods for Remote Operated Vehicle motion estimation in underwater environments — particularly relevant given Indonesia's vast maritime territory. With a growing citation record across multiple domains — robotics (3 citations), biomedical engineering (2 citations), and marine technology (2 citations) — Rahmalia represents an emerging voice in applied estimation theory. Her interdisciplinary approach makes her work valuable for students and researchers working at the intersection of control systems, signal processing, and robotics.