Freddy Kurniawan

Universitas Teknologi Yogyakarta, Institute of Technology and Business

Papers

Total Citations

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About

Freddy Kurniawan is a researcher specializing in sensor fusion, state estimation, and mobile robotics, with a particular focus on Kalman filtering techniques for real-world navigation and control systems. His most cited work, "Mobile Robot Localization via Unscented Kalman Filter" (2019, 10 citations), addresses the challenge of estimating a robot’s position and heading in unknown environments, demonstrating how the Unscented Kalman Filter (UKF) outperforms traditional approaches in handling nonlinearities inherent in mobile robot motion. In his second highly cited paper, "Estimasi Sudut Rotasi Benda Kaku Berbasis IMU Menggunakan Kalman Filter" (2021, 9 citations), Kurniawan tackles the problem of accurate rotation angle estimation for rigid bodies—critical for spacecraft, UAVs, and underwater vehicles—by applying Kalman filtering to reduce noise from Inertial Measurement Units (IMUs). His work bridges theoretical estimation algorithms with practical implementation, offering robust solutions for autonomous systems operating under uncertainty. With a growing citation record, Kurniawan’s contributions are particularly valuable for students and engineers developing localization and orientation systems in robotics and aerospace, where precision and reliability are paramount.