Reiko Inoue
Papers
1
Total Citations
2
H-Index
1
About
Reiko Inoue’s research lies at the intersection of robotics, automation, and combinatorial optimization, with a primary focus on multi-arm robotic systems and complex assembly tasks. Her most cited work, “Near-Optimal Assembly Task Sequencing and Allocation Method for Multi-Arm Robot System” (2023), tackles the NP-hard problem of determining feasible, collision-free assembly sequences under strict geometrical constraints. Inoue proposes a novel algorithmic framework that simultaneously optimizes task sequencing and allocation across multiple robot arms, significantly reducing computational complexity while maintaining near-optimal performance. This contribution is critical for advancing industrial automation, where efficient coordination of multiple manipulators is essential for high-mix, low-volume production. Although her citation count is still growing—reflecting the recency of her work—the paper has already garnered attention for its practical relevance and theoretical rigor. Inoue’s research is particularly valuable for students and engineers working on robotic cell design, assembly planning, and multi-agent coordination. Her work demonstrates how careful modeling of geometric and temporal constraints can yield scalable solutions to traditionally intractable problems, marking her as a promising voice in modern robotics and manufacturing research.
Research Focus
Key Achievements
Top Papers
- 1