Papers

8

Total Citations

200

H-Index

4

About

Dengyu Xiao is a leading researcher in intelligent manufacturing and robotics, with a primary focus on chatter monitoring and suppression in robotic drilling—a critical challenge for aviation and precision machining. His most influential work introduces advanced time-frequency analysis methods, such as the local maximum synchrosqueezing-based method and the concentrated velocity synchronous linear chirplet transform, which enable real-time, high-accuracy detection of machining chatter. These contributions, each garnering over 60 citations, have significantly improved surface finish quality and operational reliability in automated drilling systems. Xiao also developed a pre-generated matrix-based method for real-time chatter monitoring, further cementing his impact in the field. Beyond machining, his research spans multi-robot cooperative systems, visual-inertial SLAM for dynamic environments, and phenotype-based robotic platforms for plant breeding, demonstrating versatility in applying robotics to diverse domains. His recent work on pre-assigned time safe formation control for nonholonomic mobile robots and error identification in dual-robot systems highlights his ongoing contributions to intelligent, cooperative automation. With a growing portfolio of high-impact publications, Dengyu Xiao is recognized for bridging theoretical signal processing and practical robotic applications, advancing the frontier of smart manufacturing.

Research Focus

Key Achievements

4
H-Index
8
Papers
200
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Timely chatter identification for robotic drilling using a local maximum synchrosqueezing-based method
69 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 28
🏛 Institutions: Shanghai Jiao Tong University, Chongqing University, China Southern Power Grid (China)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago