Syo Tatsukawa

Papers

Total Citations

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About

Syo Tatsukawa is a robotics researcher whose work focuses on advancing indoor mobile robot navigation, particularly for assistive technologies that support elderly and physically disabled individuals. His key research areas include passive RFID-based localization systems, obstacle prediction, and autonomous robot movement correction. In his most cited work, "Moving correction method of a mobile robot using passive RFID system based on obstacle prediction" (2014), Tatsukawa addresses a critical challenge in indoor robotics: enabling low-cost, simple-composition navigation systems that can reliably predict and avoid obstacles. By leveraging passive RFID technology—known for its affordability and ease of deployment—he developed a method that allows mobile robots to dynamically correct their paths in real time. This contribution is significant because it demonstrates how cost-effective sensors can be integrated with predictive algorithms to enhance robot autonomy in cluttered indoor environments. While his citation count (2) reflects a specialized niche, his work contributes to the broader goal of making assistive robotics more accessible and practical for real-world applications. Tatsukawa’s research sits at the intersection of affordable hardware and intelligent software, offering a pragmatic approach to improving the safety and reliability of mobile robots in human-centered spaces.