T. Nakagami
Papers
2
Total Citations
58
H-Index
2
About
T. Nakagami is a leading figure in mobile robotics, with a focused expertise in sensor fault detection and diagnosis (FDI) for autonomous navigation systems. His major contributions center on developing probabilistic, multiple-model frameworks to ensure the reliability of dead-reckoning systems—the internal sensors that estimate a robot’s position. In his seminal 2002 work, which has garnered 56 citations, Nakagami pioneered the use of an interacting multiple-model (IMM) approach to explicitly model sensor normal and failure modes as probabilistic switches. This method allows for real-time detection and identification of faults, a critical step toward robust autonomous operation. Further expanding this work, he introduced a Variable Structure IMM (VSIMM) method combined with adaptive filters to diagnose specific failure types—including hard faults, noise faults, and scale faults—validated through experiments on a four-wheeled skid-steer mobile robot. Nakagami’s research directly addresses the challenge of maintaining accurate robot localization in the presence of sensor degradation, making his work foundational for engineers and researchers developing resilient mobile platforms for field, service, and industrial applications.
Research Focus
Key Achievements
Top Papers
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