Kazuaki Yokoyama
Papers
1
Total Citations
3
H-Index
1
About
Dr. Kazuaki Yokoyama is a robotics researcher whose work focuses on autonomous navigation and environmental mapping for mobile robots operating in human-centered spaces. His most-cited paper, "Mapping and Correction Method in Static Environments for Autonomous Mobile Robot" (2014, 3 citations), addresses a fundamental challenge in robotics: constructing accurate geometric maps of environments cluttered with obstacles and dynamic human activity. Yokoyama’s contribution lies in developing correction methods that improve map reliability by filtering errors introduced by static structures, enabling robots to navigate more safely and efficiently in real-world settings. While his citation count reflects a niche but specialized impact, his work is notable for tackling the practical difficulties of deploying autonomous systems in everyday human environments—a critical step toward integrating robots into homes, offices, and public spaces. By focusing on static environment mapping, Yokoyama has contributed to the foundational infrastructure that supports more advanced robotic behaviors, such as path planning and obstacle avoidance. His research underscores the importance of robust perception systems in bridging the gap between laboratory prototypes and real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1