Tatsuya Miyano

Toyota Motor Corporation (United States), Toyota Motor Corporation (Switzerland)

Papers

Total Citations

H-Index

About

Tatsuya Miyano is a robotics researcher focused on multirobot coordination, optimal task allocation, and resilient monitoring systems. His work addresses critical challenges in deploying heterogeneous robot teams—combining aerial and ground vehicles—for complex real-world tasks. In his highly cited 2023 paper, "Globally Optimal Assignment Algorithm for Collective Object Transport Using Air–Ground Multirobot Teams," Miyano introduced a novel algorithm that finds the globally optimal matching between objects and robots to minimize total system energy, revealing key local optimality criteria. This contribution is foundational for efficient collaborative transport in logistics and disaster response. Earlier, his 2019 paper on "Coverage Control for Resilient Monitoring System" tackled the common pitfall of the Lloyd algorithm converging to locally optimal deployments, proposing distributed control strategies to ensure robust, large-scale environmental monitoring. Though early in his career, with citations accumulating steadily, Miyano’s work demonstrates a clear trajectory toward practical, scalable multirobot systems. His achievements include advancing theoretical foundations for optimal assignment and resilient coverage, making his research essential reading for students and engineers working on autonomous multiagent coordination and field robotics.