Papers
42
Total Citations
1,082
H-Index
18
About
Fangyu Peng is a leading researcher in robotic machining and precision manufacturing, with a particular focus on robotic milling of complex parts. His work addresses some of the most critical challenges in industrial robotics, including structural stiffness optimization, chatter detection and suppression, posture planning, and positional error compensation. Peng's most influential contribution — a 2021 comprehensive review of robotic milling that has garnered 186 citations — established him as a key synthesizer of the field, mapping challenges, methodologies, and future directions for the broader research community. His highly cited 2018 study on stiffness-based posture and feed orientation optimization (168 citations) fundamentally advanced how researchers approach robot configuration during milling, directly improving machining precision and surface quality. A consistent theme across his body of work is tackling the inherent low-stiffness limitations of robotic structures, which give rise to chatter and vibration problems. His investigations into low-frequency chatter, regenerative instability, and posture-dependent frequency response functions have produced practical predictive and compensatory frameworks widely adopted by subsequent researchers. More recently, Peng has extended his expertise into uncertainty quantification and real-time error correction, reflecting a broader vision for reliable, high-precision robotic manufacturing in industrial settings.
Research Focus
Key Achievements
Top Papers
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- 5Investigation of the low-frequency chatter in robotic milling60 citations · 2023
- 6Rapid prediction of posture-dependent FRF of the tool tip in robotic milling55 citations · 2020
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