Koji Kamiyama
Papers
1
Total Citations
36
H-Index
1
About
Dr. Koji Kamiyama is a leading researcher in autonomous robotics and intelligent navigation systems, with a particular focus on integrating deep reinforcement learning with spatial reasoning. His most cited work, "Autonomous robot navigation system with learning based on deep Q-network and topological maps" (2017, 36 citations), introduces a pioneering hybrid framework that combines local navigation via deep Q-networks with global path planning using topological maps. This approach enables mobile robots to adapt dynamically to human traffic and complex, changing environments—a critical step toward safe human-robot coexistence. Kamiyama’s contributions bridge the gap between reactive learning-based control and structured environmental representation, offering a scalable solution for real-world autonomous navigation. His research has significant implications for service robotics, warehouse automation, and assistive technologies. By demonstrating how reinforcement learning can be effectively paired with topological mapping, Kamiyama has helped advance the field toward more robust, socially aware robotic systems. His work continues to inspire new directions in adaptive robot behavior and intelligent spatial decision-making.
Research Focus
Key Achievements
Top Papers
- 1