Papers
3
Total Citations
22
H-Index
3
About
Koki Tomitagawa is a robotics researcher focused on solving critical challenges in automated waste management through energy-efficient path planning. His core research centers on developing intelligent navigation algorithms for waste collection robots operating in indoor environments like factories and large buildings. Tomitagawa’s major contribution lies in adapting Ant Colony Optimization (ACO) algorithms to minimize energy consumption during waste collection routes, directly addressing the limited battery life that constrains autonomous robot operations. His most cited work, "Performance Measurement of Energy Optimal Path Finding for Waste Collection Robot Using ACO Algorithm" (2022, 11 citations), demonstrates how bio-inspired computing can reduce labor costs and manpower shortages in solid waste management. Building on this, his subsequent papers (2022, 7 citations; 2021, 4 citations) progressively refined the ACO approach, showing measurable improvements in energy efficiency for multi-bin collection scenarios. Collectively, his work has accumulated 22 citations, establishing a foundation for practical, energy-aware robotics in facility maintenance. Tomitagawa’s research bridges the gap between theoretical optimization algorithms and real-world waste collection challenges, offering scalable solutions that could transform how industries handle solid waste while reducing operational costs and environmental impact.
Research Focus
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Top Papers
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