Papers

7

Total Citations

76

H-Index

5

About

Dr. Luka Eciolaza is a leading researcher at the intersection of robotics, automation, and control systems, with a focus on enhancing the precision and reliability of industrial manufacturing. His work is defined by a dual commitment to advancing theoretical control methods and developing practical, data-driven solutions for real-world production environments. Dr. Eciolaza has made significant contributions to the field of manufacturing robotics, particularly through his pioneering work on vision-based, data-driven methods for assessing accuracy degradation in robotic systems—a critical challenge for maintaining quality in automated production lines. His most cited work, "Towards manufacturing robotics accuracy degradation assessment: A vision-based data-driven implementation" (29 citations), exemplifies this impact. He is also a key figure in the adoption of virtual commissioning technologies, using them as powerful educational tools to train the next generation of automation engineers. Additionally, Dr. Eciolaza has advanced the control of complex robotic systems, including quadrotors and non-holonomic mobile robots, by applying dynamic feedback linearization based on piecewise bilinear (PB) models. His development of the ADAPT framework for automatic diagnosis of activities and processes in automation environments further underscores his commitment to creating intelligent, self-diagnosing industrial systems.

Research Focus

Key Achievements

5
H-Index
7
Papers
76
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Towards manufacturing robotics accuracy degradation assessment: A vision-based data-driven implementation
29 citations · 2020
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Mondragon Unibertsitatea, European Centre for Soft Computing

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago