Takeshi Matsuoka
Papers
7
Total Citations
50
H-Index
5
About
Takeshi Matsuoka is a robotics researcher whose work centers on autonomous mobile robot navigation, self-localization, and sensor-based perception systems. His most significant contributions lie in developing efficient and robust methods for robot self-localization — a fundamental challenge in autonomous robotics — particularly in dynamic, obstacle-rich environments such as those found in competitive robot soccer. Matsuoka's most influential work, published in 2004 and 2005 with a combined 29 citations, introduced novel self-localization techniques that require only two landmarks combined with dead reckoning, departing from the conventional requirement of three or more landmarks. This advancement improved real-time positioning capability for autonomous soccer robots operating under the demanding conditions of RoboCup's middle-size league. His research further explored omnidirectional camera systems, stereo vision, and visual feature-based localization, demonstrating a sustained commitment to vision-driven approaches to robot positioning. With contributions spanning ultrasonic sensor navigation and environmental visual feature recognition, Matsuoka has helped lay groundwork for reliable mobile robot autonomy in complex, real-world settings. His body of work, accumulating over 50 citations across multiple publications, reflects steady influence within the mobile robotics and intelligent systems research community.
Research Focus
Key Achievements
Top Papers
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