About

Kuniaki Kawabata is a versatile robotics researcher whose work spans autonomous vehicle motion planning, multi-robot coordination, disaster response robotics, and robot self-diagnostics. He is perhaps best known for his highly influential contributions to sampling-based motion planning, particularly his refinements of the Rapidly-exploring Random Tree (RRT) algorithm for on-road autonomous driving — work that has garnered over 200 citations and remains a foundational reference in the autonomous vehicles community. His earlier research pioneered decentralized control algorithms enabling multiple mobile robots to cooperatively transport large objects without requiring individual position data, demonstrating elegant solutions to complex coordination challenges across several well-cited studies from the early 2000s. Kawabata has also made meaningful contributions to disaster robotics, developing aerial robots and wireless sensor network deployment systems designed for urban search-and-rescue (USAR) scenarios. More recently, his work has addressed one of the most consequential real-world robotics challenges of our time: contributing technological solutions to the remote decommissioning operations at the Fukushima Daiichi Nuclear Power Station. Across more than two decades of research, Kawabata has consistently bridged theoretical algorithmic innovation with urgent practical applications, making him a distinctive and impactful figure in applied robotics.

Research Focus

Key Achievements

13
H-Index
90
Papers
933
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Efficient Sampling-Based Motion Planning for On-Road Autonomous Driving
208 citations · 2015
📈 Most Prolific Year: 2002 (15 Papers)
🤝 Key Collaborators: 140
🏛 Institutions: RIKEN, Japan Atomic Energy Agency, Nitto RIKEN (Japan), Futaba (Japan), Robotics Research (United States), Nippon Soken (Japan)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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