Fredrik Dukan

Norwegian University of Science and Technology

Papers

Total Citations

146

H-Index

About

Fredrik Dukan is a leading researcher in marine robotics, with a primary focus on underwater vehicle navigation, fault diagnosis, and dynamic positioning systems. His most influential work, "Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot" (2014, 94 citations), pioneered the use of particle filter-based methods to simultaneously handle sensor and thruster failures in underwater robots. By modeling the vehicle and its anomalies as a switching-mode hidden Markov model, Dukan provided a robust framework for maintaining navigation accuracy even under multiple failure scenarios—a critical contribution for autonomous operations in hazardous deep-sea environments. His earlier work, "Dynamic positioning system for a small size ROV with experimental results" (2011, 52 citations), demonstrated the practical implementation of a dynamic positioning system on the Minerva ROV, detailing the hardware, software, and state estimation architectures. This hands-on experimental validation bridged the gap between theoretical control algorithms and real-world underwater deployment. Dukan’s contributions have directly advanced the reliability and autonomy of underwater robots, making his research essential reading for engineers and scientists working on fault-tolerant marine systems.