Papers

11

Total Citations

101

H-Index

6

About

Xiaobu Yuan is a researcher whose work sits at the dynamic intersection of biologically inspired computing, robotics, and intelligent manufacturing systems. His research has made meaningful contributions to two principal domains: neural network-based robot motion planning and virtual assembly systems enhanced by artificial intelligence. Yuan's most recognized contribution, "Virtual Assembly with Biologically Inspired Intelligence" (2003, 34 citations), introduced a pioneering framework that enables product engineers to make assembly-related manufacturing decisions within virtual environments, eliminating the need for costly physical prototypes. Complementing this, his interactive virtual reality approach to assembly planning empowered engineers to program robotic manipulators intuitively in three-dimensional workspaces. In robotics, Yuan has consistently advanced real-time, collision-free navigation through shunting neural network architectures. His work on nonholonomic car-like robots (2002) and torque-controlled mobile robots (2004) demonstrated how biologically inspired neural dynamics could elegantly solve complex motion planning challenges in nonstationary environments. His later research on Cellular Neural Networks extended these principles to optimal multi-target path planning. With over 99 cumulative citations, Yuan's body of work reflects a coherent and sustained effort to bridge biological intelligence with practical robotics and manufacturing applications, offering tools that remain relevant to researchers in autonomous systems and intelligent production engineering.

Research Focus

Key Achievements

6
H-Index
11
Papers
101
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Virtual assembly with biologically inspired intelligence
34 citations · 2003
📈 Most Prolific Year: 2002 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Windsor, Memorial University of Newfoundland

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago