Papers
31
Total Citations
1,538
H-Index
20
About
Tegoeh Tjahjowidodo is a leading figure in the fields of precision robotics, nonlinear system dynamics, and intelligent manufacturing. His research focuses on overcoming the fundamental challenges of controlling flexible, cable-driven mechanisms—critical for applications in minimally invasive surgery and advanced industrial automation. A central contribution is his pioneering work on modeling and compensating for complex friction and hysteresis in tendon-sheath actuated systems, which has enabled unprecedented precision in flexible endoscopic surgical robots. His highly cited 2013 paper on hysteresis modeling for such systems (166 citations) and his 2015 work on nonlinear friction compensation (114 citations) are foundational texts in the field. In manufacturing, Tjahjowidodo has advanced intelligent process monitoring, notably developing a support vector machine and genetic algorithm approach for in-process tool condition monitoring in abrasive belt grinding (209 citations). He has also integrated deep learning for virtual verification of weld seam removal, pushing toward fully autonomous robotic finishing. With multiple papers exceeding 100 citations and a consistent focus on bridging theoretical modeling with real-world control, his work has profoundly impacted both surgical robotics and smart manufacturing.
Research Focus
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