Ryu Narikawa
Papers
3
Total Citations
15
H-Index
3
About
Ryu Narikawa is a robotics researcher specializing in path planning and motion control for automated warehouse systems. His work focuses on developing advanced Model Predictive Control (MPC) methods to enable efficient, collision-free navigation for multiple robots operating in confined, high-density environments. Narikawa’s major contributions include proposing a novel MPC-based path planning approach that optimizes overall warehouse performance without relying on pre-defined global paths, significantly improving adaptability and real-time responsiveness. His research also extends to cooperative motion generation for heterogeneous agents—different types of robots working together—while ensuring collision avoidance and system-wide optimization. With his most-cited paper, "A Proposal of Path Planning for Robots in Warehouses by Model Predictive Control without Using Global Paths," accumulating 9 citations, and two additional works from 2022 each garnering 3 citations, Narikawa is establishing a solid foundation in warehouse robotics. His comparative studies on collision avoidance methods provide valuable insights for designing safer, more efficient automated logistics systems, making his work highly relevant to the growing e-commerce and automation sectors.
Research Focus
Key Achievements
Top Papers
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