Toshiki Kikugawa
Papers
1
Total Citations
6
H-Index
1
About
Toshiki Kikugawa is a researcher in human-robot interaction, with a focus on developing socially aware robotic systems that can proactively and naturally engage with humans. His most cited work, "Network Guide Robot System Proactively Initiating Interaction with Humans Based on Their Local and Global Behaviors" (2015, 6 citations), introduces a novel framework for guide robots that analyze both immediate, local cues—such as a person’s direction and speed—and broader, global behavioral patterns to determine the optimal moment to initiate conversation. This contribution addresses a critical challenge in robotics: enabling machines to move beyond passive response and toward context-sensitive, autonomous social interaction. By integrating behavioral modeling with networked sensor data, Kikugawa’s research lays groundwork for more intuitive service robots in public spaces like museums, airports, or shopping centers. While his citation count reflects early-stage impact, the conceptual innovation of his work—bridging local and global behavioral analysis—offers a valuable foundation for future studies in proactive human-robot communication. His approach continues to inspire researchers seeking to make robots more perceptive and less intrusive in everyday human environments.
Research Focus
Key Achievements
Top Papers
- 1