Ryoichi Kishimoto
Papers
1
Total Citations
2
H-Index
1
About
Ryoichi Kishimoto is a researcher in bio-inspired robotics and autonomous systems, with a focus on developing adaptive locomotion and goal-oriented behaviors for snake-like robots. His most cited work, "Acquisition of Goal-Oriented Behavior for Snake-Like Robot by CPG and Reinforcement Learning" (2017), demonstrates a novel integration of central pattern generators (CPGs) with reinforcement learning to enable a snake-like robot built from the Bioloid kit to autonomously acquire the ability to reach a target. By using CPGs to generate rhythmic motor patterns and optimizing motor offset values through reinforcement learning, Kishimoto showed that the robot could adapt its behavior to its unique physical characteristics. He further enhanced the system by equipping the robot with a Raspberry Pi and a webcam, allowing it to independently perceive and navigate toward goals. Although this paper has garnered 2 citations, it represents a foundational step in merging neural oscillators with machine learning for real-world robotic control. Kishimoto’s work contributes to the broader fields of autonomous robotics and adaptive control, offering insights into how simple, biologically inspired mechanisms can produce complex, goal-driven actions in constrained robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1