Papers

8

Total Citations

55

H-Index

4

About

Toshimitsu Ushio is a leading figure in the intersection of discrete event systems (DES), formal methods, and robotics. His research focuses on developing rigorous, hierarchical control frameworks—primarily using Petri nets and temporal logic—to enable safe, optimal, and autonomous behavior in complex robotic systems, from humanoid robots to multi-UAV teams. A major contribution is his pioneering work on supervisory control for motion planning, where he introduced timed Petri net and modular state net architectures to generate optimal motion sequences for humanoid robots (18 citations). He has significantly advanced online control synthesis, proposing schemes that allow discrete event systems to satisfy specifications expressed in fragments of linear temporal logic (scLTL) in real time (15 citations). More recently, Ushio has integrated reinforcement learning with formal specifications to handle uncertainties in mobile robot control (7 citations), and extended counting LTL for path planning in heterogeneous multi-robot systems handling complex routing tasks (2 citations). His work on limited lookahead policy (LLP) supervisors for mobile robots (5 citations) and support systems for single-operator supervision of multiple UAVs (2 citations) demonstrates a sustained commitment to bridging theoretical control with practical, real-world deployment.

Research Focus

Key Achievements

4
H-Index
8
Papers
55
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Motion planning for humanoid robots using timed Petri net and modular state net
18 citations · 2003
📈 Most Prolific Year: 2002 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: The University of Osaka, Osaka University of Economics, Osaka University of Human Sciences, Nanzan University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago