Papers

22

Total Citations

484

H-Index

12

About

T. Thang Vo-Doan is a pioneering researcher at the intersection of biorobotics, cyborg systems, and biomechanical engineering, best known for his groundbreaking work on insect-machine hybrid robots. His research centers on harnessing living insects as ultra-lightweight robotic platforms, using electrical muscle stimulation to achieve precise locomotion control in ways that outperform conventional miniature robots. His landmark 2014 study on closed-loop control of beetle leg muscles (65 citations) established a foundational framework for biological microactuators, while subsequent work on cyborg beetles demonstrated sophisticated capabilities including sideways walking (57 citations) and free-flight muscle analysis (51 citations). A recurring theme across his portfolio is the application of cyborg insects to Urban Search and Rescue scenarios, culminating in a 2023 intelligent hybrid system (59 citations) capable of autonomous obstacle negotiation and human detection. Beyond cyborg research, Vo-Doan has contributed insect-inspired robotic leg designs, advanced outdoor insect videography techniques, and soft robotic surgical systems, reflecting remarkable versatility. With over 400 cumulative citations, his work fundamentally challenges the boundary between living organisms and engineered machines, offering transformative implications for rescue robotics, aerial vehicle design, and biomedical engineering.

Research Focus

Key Achievements

12
H-Index
22
Papers
484
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
A Biological Micro Actuator: Graded and Closed-Loop Control of Insect Leg Motion by Electrical Stimulation of Muscles
65 citations · 2014
📈 Most Prolific Year: 2023 (4 Papers)
🤝 Key Collaborators: 93
🏛 Institutions: Nanyang Technological University, University of Freiburg, The University of Queensland

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago