Papers

22

Total Citations

248

H-Index

8

About

Xiao Lu is a robotics and automation researcher whose work spans robot calibration, mobile robot systems, unmanned aerial vehicles, and intelligent sensing. Lu's most influential contribution lies in robot calibration methodology, particularly the development of a screw axis identification method based on the product of exponentials (POE) model for serial robot calibration, which has garnered 54 citations and established a foundational approach in the field. Complementing this, Lu advanced fully automatic hand-eye calibration techniques for serial robot systems, streamlining the simultaneous calibration of robot body, hand-eye relation, and measurement systems. Beyond manipulation, Lu has made notable strides in mobile robotics, proposing a cost-effective Wi-Fi-based indoor positioning system (34 citations) and a gene-rearrangement-enhanced genetic algorithm for mobile robot path planning. More recently, Lu has expanded into UAV fault diagnostics and self-supervised monocular depth estimation, reflecting a broadening research vision. With contributions also spanning ZigBee-based sensor networks, neural network kinematics solving, and 3R subproblem frameworks, Lu's body of work—totaling over 200 citations—represents a versatile and sustained commitment to advancing intelligent robotic systems across both theoretical and applied dimensions.

Research Focus

Key Achievements

8
H-Index
22
Papers
248
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A screw axis identification method for serial robot calibration based on the POE model
54 citations · 2012
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 55
🏛 Institutions: Shandong University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago