Ryo Fukuoka
Papers
1
Total Citations
4
H-Index
1
About
Ryo Fukuoka is a researcher in robotics and autonomous systems, with a focus on developing intelligent control models for self-driving vehicles. His most cited work, "Self-driving model car acquiring three-point turn motion by using improved LSTM model" (2021), demonstrates a novel application of long short-term memory (LSTM) neural networks to enable a model car to autonomously execute complex maneuvers like three-point turns. This contribution addresses a critical challenge in autonomous navigation—handling tight spaces and reversing—by enhancing the learning and memory capabilities of AI-driven vehicles. While his citation count is modest, with 4 citations for this paper, the work highlights his innovative approach to integrating deep learning with real-world robotic tasks. Fukuoka’s research bridges the gap between theoretical AI models and practical autonomous driving, offering insights into how improved LSTM architectures can refine motion planning and control. His efforts contribute to the broader field of intelligent transportation, where reliable, adaptive driving behaviors are essential for safety and efficiency.
Research Focus
Key Achievements
Top Papers
- 1