Michael Tannous
Papers
5
Total Citations
119
H-Index
4
About
Michael Tannous is a researcher at the intersection of collaborative robotics, manufacturing automation, and bio-inspired motor control. His primary contributions lie in enhancing human-robot interaction for industrial applications, particularly through haptic-based touch detection systems that enable safer and more responsive collaborative welding robots. His most cited work, "Haptic-based touch detection for collaborative robots in welding applications" (47 citations), provides a foundational framework for collision-aware robotic manipulation. Tannous has also advanced smart manufacturing by developing automatic welding imperfection detection using 2-D laser scanners (34 citations), contributing to quality control in Industry 4.0 environments. Demonstrating a unique interdisciplinary breadth, he has explored the impact of aging and cognitive mechanisms on motor activation patterns using locusts as model organisms in an Orthoptera-robot interaction study (30 citations), bridging neuroscience and robotics. His recent work evaluating quadruped robots for autonomous energy industry inspections (2023) reflects a growing focus on field robotics. Through datasets and pilot studies, Tannous continues to push the boundaries of safe, intelligent, and adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5