Papers

9

Total Citations

102

H-Index

6

About

Harun Tugal is a robotics researcher whose work spans mobile manipulation, human-robot interaction, and autonomous systems, with a particular focus on applying advanced control strategies to high-stakes environments. His research has made significant contributions to the control and motion planning of vehicle-manipulator systems, developing algorithms that enable mobile robots to inspect unknown objects through intelligent base positioning and stable physical interaction — work that has garnered 24 citations. Tugal has pioneered innovative experimental platforms, including a Stewart Platform-based emulator for underwater vehicle-manipulator systems, reflecting his expertise in replicating complex real-world conditions in controlled settings. His research extends into critical application domains, including nuclear decommissioning — notably addressing fuel debris retrieval challenges at Fukushima Daiichi — and surgical robotics, where he has measured hand-impedance dynamics during laparoscopic training to inform smarter co-manipulated robotic systems. His work on haptic digital twins for nuclear applications further demonstrates his commitment to bridging simulation and physical interaction for operator safety and training. With publications spanning adaptive control, force transmission optimization, and underwater asset inspection, Tugal's cumulative citation impact reflects a productive and wide-ranging career at the intersection of autonomous robotics and real-world human-centered applications.

Research Focus

Key Achievements

6
H-Index
9
Papers
102
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Contact-based object inspection with mobile manipulators at near-optimal base locations
24 citations · 2022
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 29
🏛 Institutions: Heriot-Watt University, Culham Science Centre, United Kingdom Atomic Energy Authority, University of Edinburgh

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago