Toru Namerikawa
Keio University, Kanazawa University, Nagaoka University of Technology
Papers
33
Total Citations
354
H-Index
10
About
Toru Namerikawa is a prominent researcher in robotics and control systems, whose work spans mobile robot localization, simultaneous localization and mapping (SLAM), and teleoperation control. His most influential contribution, an analysis of Extended Kalman Filter-based mobile robot localization with intermittent measurements (2013, 75 citations), established a rigorous theoretical framework for handling unreliable sensor data—a critical challenge in real-world robotic deployments. Complementing this, his series of papers on H∞ filter-based SLAM demonstrated how robots can reliably map and navigate environments even under unknown noise statistics, advancing beyond classical Kalman Filter assumptions. In teleoperation, Namerikawa has made significant strides in enabling safe and responsive remote robot control under realistic network conditions, developing bilateral and predictive PD control strategies that gracefully handle time-varying communication delays. More recently, his work on autonomous multi-robot coordination for environmental monitoring—including oil spill tracking via hybrid fuzzy and potential field methods—demonstrates a broadening impact across humanitarian and ecological applications. His research into the kidnapped robot problem further underscores his commitment to robust, fault-tolerant robotics. Collectively, his body of work, accumulating over 260 citations, represents foundational contributions to dependable autonomous systems in uncertain, real-world environments.
Research Focus
Key Achievements
Top Papers
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- 5Robotic Mapping and Localization Considering Unknown Noise Statistics20 citations · 2011
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- 7Robot localization and mapping problem with unknown noise characteristics16 citations · 2010
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- 9Predictive PD Control for Teleoperation with Communication Time Delay14 citations · 2008
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