Papers

14

Total Citations

84

H-Index

6

About

Yoshiki Matsuo is a pioneering researcher in collective robotics and human-machine cooperation, whose work has fundamentally shaped how autonomous robot swarms can be controlled and coordinated. His primary research areas include multi-robot systems, swarm intelligence, and human-robot interaction, with a particular focus on developing simple yet effective control mechanisms for robot collectives. Matsuo's most influential contribution is his development of virtual force-based control methods for autonomous mobile robot herds, enabling collective behaviors such as migration, shape formation, and internal movement control without complex communication protocols. His 2004 paper on this topic has garnered 14 citations and remains foundational in the field. He also introduced the innovative "S3 RoboNet" system for victim search in disaster zones, demonstrating the practical applications of his swarm control theories. Matsuo's work on human-machine cooperation systems for skilled tasks, such as cutting operations, bridges the gap between human expertise and robotic assistance. His research on cognitively inspired reinforcement learning for complex motion control, including giant-swing movements, showcases his versatility. As a key contributor to Tokyo Institute of Technology's Super-Mechano Colony project, Matsuo has advanced the frontiers of collective robotics, with his papers collectively cited over 70 times across multiple domains of autonomous systems.

Research Focus

Key Achievements

6
H-Index
14
Papers
84
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Collective Behavior Control of Autonomous Mobile Robot Herds by Applying Simple Virtual Forces to Individual Robots
14 citations · 2004
📈 Most Prolific Year: 2003 (3 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Tokyo Institute of Technology, Tokyo University of Technology

Top Papers

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    5 citations · 2006
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Key Collaborators

Contact & Links

Available for collaboration
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