Naoya Shibata
Papers
1
Total Citations
16
H-Index
1
About
Naoya Shibata’s research centers on multi-robot systems, formation control, and sensor-based navigation in cluttered environments. His most-cited work, “Leader–follower formation control with obstacle avoidance using sonar-equipped mobile robots” (2014, 16 citations), introduces an adaptive sonar-processing method that enables follower robots to distinguish a leader from obstacles, ensuring stable formation even in obstacle-scattered settings. This contribution addresses a critical challenge in cooperative robotics: reliable perception under limited sensing. Shibata’s approach leverages multiple sonars to dynamically differentiate targets, advancing practical deployment of robot teams in real-world scenarios like search-and-rescue or industrial inspection. While his citation count reflects a focused, early-career impact, the work demonstrates foundational thinking in sensor fusion and decentralized control. His research is particularly relevant for students and engineers exploring low-cost, scalable solutions for autonomous multi-agent systems. Shibata’s work underscores the importance of robust perception in formation control, offering a stepping stone for future innovations in collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1