Lorenzo Biasi

University of Stuttgart

Papers

1

Total Citations

2

H-Index

1

About

Lorenzo Biasi’s research lies at the intersection of industrial robotics and intelligent control, with a focus on enhancing the absolute accuracy of robotic systems. His major contribution is the development of a hybrid compensation method that integrates artificial neural networks to address both geometric and non-geometric errors—such as nonlinear payload effects and tool wear—which are often neglected in conventional calibration techniques. This work, published in 2023, has already garnered attention with 2 citations, signaling its relevance to advancing precision in manufacturing. Biasi’s approach bridges the gap between theoretical modeling and real-world industrial application, offering a practical solution to improve robot performance under dynamic operating conditions. His research is particularly notable for its potential to reduce downtime and extend tool life in automated production lines. By tackling the persistent challenge of non-geometric error compensation, Biasi is contributing to the next generation of adaptive, self-correcting robotic systems, making him a promising voice in the field of robotics and intelligent manufacturing.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Artificial Neural Network Guided Compensation of Nonlinear Payload and Wear Effects for Industrial Robots
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Stuttgart

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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