Nora Aguirre Jaca

Papers

1

Total Citations

2

H-Index

1

About

Nora Aguirre Jaca is a researcher specializing in industrial robotics, with a focus on trajectory accuracy, joint dynamics, and stiffness modeling. Her most-cited work, “Industrial Robotics Trajectory Compensation Model and Joints Torsional Stiffness Impact Analysis” (2020), addresses a critical challenge in manufacturing: the deviation between programmed and executed robot trajectories under external force disturbances. By analyzing joint torsional stiffness, she developed a compensation model that mitigates displacement errors caused by deformation in robotic joints—a key contribution to improving precision in automated systems. Though her citation count is currently modest, her work lays foundational groundwork for enhancing robot performance in force-sensitive applications, such as assembly and material handling. Aguirre Jaca’s research is particularly relevant for engineers seeking to bridge the gap between theoretical robotics and real-world industrial constraints, offering practical insights into error reduction without costly hardware upgrades. Her focus on stiffness impact analysis positions her as a rising voice in the field of robotic accuracy and control.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Industrial Robotics Trajectory Compensation Model and Joints Torsional Stiffness Impact Analysis
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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