M. Hirayama

Papers

Total Citations

150

H-Index

About

M. Hirayama is a leading researcher in mobile robotics and sensor-based localization, with a primary focus on RFID (radio frequency identification) systems for autonomous navigation. Their most influential work, "Self-localization of mobile robots with RFID system by using support vector machine" (2005), has garnered 136 citations and pioneered the use of inexpensive RFID technology combined with machine learning to solve the critical problem of robot self-localization. This approach leverages support vector machines to interpret RFID signals, offering a cost-effective and reliable alternative to traditional localization methods. Hirayama further advanced this field in "A Supervised Learning Approach to Robot Localization Using a Short-Range RFID Sensor" (2007), which demonstrated how RFID tags as landmarks can simplify data association—a notoriously difficult challenge in robotics. Additionally, their work on "Query-based occupancy map for SVM-CBIR on mobile robot image database" (2005) explored content-based image retrieval for human-robot interfaces, enabling robots to efficiently navigate and retrieve visual data from large-scale databases. Hirayama’s contributions have significantly impacted service robotics, logistics, and manufacturing, where accurate, low-cost localization is essential for autonomous operation.