Papers

44

Total Citations

556

H-Index

13

About

Masafumi Hashimoto is a robotics researcher whose work spans mobile robot systems, fault detection, neural network control, and human-robot interaction. His most influential contributions lie at the intersection of multi-robot coordination and intelligent sensing, with early foundational work addressing the cooperative transport of heavy objects by multiple wheeled mobile robots. His 2002 paper introducing a dynamic control framework for this challenge — leveraging novel couplers to accommodate nonholonomic constraints — has accumulated 63 citations, as has his subsequent multi-model approach to fault detection and diagnosis in mobile robot sensors. Hashimoto's research on interacting multiple-model (IMM) methods for sensor fault identification in dead-reckoning systems has similarly shaped robust robot navigation, earning 56 citations. His work extends into laser-based pedestrian tracking using cooperative mobile robot teams in outdoor environments, advancing real-world human-aware navigation. More recently, Hashimoto has explored cutting-edge neural network architectures — including quaternion and quantum neural networks — for robot manipulator control, alongside emotionally expressive robot design grounded in Laban movement theory and Ekman's emotion framework. Together, his publications reflect a career dedicated to making autonomous robots more reliable, coordinated, and socially aware.

Research Focus

Key Achievements

13
H-Index
44
Papers
556
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
A multi-model based fault detection and diagnosis of internal sensors for mobile robot
63 citations · 2004
📈 Most Prolific Year: 2002 (5 Papers)
🤝 Key Collaborators: 52
🏛 Institutions: Hiroshima University, Doshisha University, Hiroshima City University, Osaka Prefecture University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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