Matt Khoshdarregi

University of Manitoba

Papers

5

Total Citations

72

H-Index

4

About

Matt Khoshdarregi is a leading researcher in precision robotic manufacturing, with a focus on enabling industrial robots to meet the stringent demands of aerospace applications. His work centers on three core areas: vibration suppression, multi-robot calibration, and high-accuracy localization. Khoshdarregi’s major contributions include pioneering the use of input shaping combined with learning-based structural models to suppress end-effector vibrations during rapid drilling motions, a technique that has garnered 31 citations. He has also developed deep neural network approaches for calibrating multi-robot cooperative systems (25 citations), significantly enhancing system-wide precision. His recent work on vision-based target localization and online error correction for robotic drilling (7 citations) addresses critical tolerance challenges in aerospace manufacturing. Additionally, Khoshdarregi has designed custom active dampers for automatic structural identification and vibration control, and has optimized robot poses to minimize joint reversals, directly improving path accuracy. With a citation count approaching 100, his research is instrumental in bridging the gap between industrial robot flexibility and the high-precision requirements of modern manufacturing.

Research Focus

Key Achievements

4
H-Index
5
Papers
72
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Suppression of robot vibrations using input shaping and learning-based structural models
31 citations · 2020
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Manitoba

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago