Prastika Indriyanti

Papers

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About

Prastika Indriyanti is a researcher at the forefront of intelligent robotics and adaptive estimation algorithms, with a focus on enhancing autonomous navigation systems. Her work centers on integrating advanced computational intelligence techniques—such as Fuzzy Logic Controllers and swarm optimization algorithms like Artificial Bee Colony—to refine state estimation in robotic localization. Her most-cited paper, "The use of Fuzzy Logic Controller and Artificial Bee Colony for optimizing adaptive SVSF in robot localization algorithm" (2024), introduces a novel approach to improving the Smooth Variable Structure Filter (SVSF), a robust estimator critical for feature-based path estimation. By dynamically tuning the SVSF’s parameters, her method significantly boosts accuracy and resilience in uncertain environments, addressing a key challenge in mobile robotics. Though early in her career, her work has already garnered attention, with 3 citations reflecting its emerging impact. Indriyanti’s contributions promise to advance real-time robot mapping and navigation, offering practical solutions for autonomous systems in complex, real-world settings. Her innovative fusion of fuzzy logic and bio-inspired optimization marks her as a promising voice in adaptive filtering and intelligent control.