Erna Apriliani

Sepuluh Nopember Institute of Technology

Papers

Total Citations

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About

Erna Apriliani is a mathematician and applied researcher whose work sits at the intersection of control theory, state estimation, and autonomous systems. Her research focuses primarily on Kalman filtering techniques, multi-robot systems, and autonomous underwater vehicle (AUV) navigation — areas where precise position estimation under uncertainty is critically important. Her most influential contribution, "Ensemble and Fuzzy Kalman Filter for position estimation of an autonomous underwater vehicle," published in 2016 and accumulating 57 citations, demonstrates her expertise in developing advanced filtering algorithms for complex dynamical systems. This work addresses the challenging problem of accurately estimating an AUV's position in dynamic, uncertain underwater environments — a fundamental challenge in marine robotics and oceanographic exploration. Beyond single-vehicle systems, Apriliani has expanded her research into multi-robot coordination, exploring formation control and decentralized estimation strategies that enable robot teams to operate effectively despite limited communication. Her 2019 and 2021 works on extended Kalman filtering for multi-robot systems reflect a forward-thinking interest in scalable, cooperative autonomous systems. Her body of work positions her as a meaningful contributor to the growing field of intelligent autonomous systems, with practical implications for underwater exploration, robotics, and real-world navigation challenges.