Shota Aoki
Papers
1
Total Citations
3
H-Index
1
About
Shota Aoki is a researcher in the field of multi-agent robotics and autonomous systems, with a primary focus on real-time perception and state estimation for competitive robotic soccer. His work is particularly influential in the context of the RoboCup Small Size League (SSL), where teams of six autonomous robots must coordinate to play soccer using a shared vision system. Aoki’s most notable contribution is the development of a shared multi-particle filter for ball position estimation, which addresses the challenge of accurately tracking a fast-moving orange golf ball using input from multiple overhead cameras. This approach improves robustness and accuracy over traditional single-filter methods, enabling more reliable decision-making for team AI. While his most-cited paper has garnered 3 citations, its impact is significant within the specialized SSL community, where precise ball tracking is critical for gameplay. Aoki’s work exemplifies the integration of probabilistic filtering with multi-agent coordination, advancing the state of the art in distributed perception for dynamic, real-world environments. His contributions are valuable for researchers and students interested in robotics, sensor fusion, and competitive autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1