Rosario Domingo

About

Rosario Domingo is a researcher whose work sits at the intersection of robotics, automation, and manufacturing engineering, with a particular focus on industrial robot optimization in automotive production environments. Her research addresses one of the most pressing challenges in modern manufacturing: maximizing the efficiency and performance of robotic manipulator systems while minimizing energy consumption and operational costs. Among her most notable contributions is the development of trajectory optimization methodologies for six-degree-of-freedom robotic arms equipped with spherical wrists. Her 2019 work introduced the application of the Kalman algorithm to robotic trajectory planning, maximizing manipulability and advancing kinematic modeling techniques for industrial manipulators. Building on this foundation, her 2022 study extended these methods to encompass both energy efficiency and performance optimization — a dual-objective approach highly relevant to sustainable manufacturing practices in the automotive sector. Both papers have each garnered 32 citations, reflecting consistent recognition within the robotics and manufacturing research communities. Domingo's contributions are particularly valuable to engineers and researchers working on intelligent automation, as her methods offer practical, implementable solutions for improving robot performance in high-demand, real-world industrial settings.

Research Focus

Key Achievements

Top Papers

1. 1
   Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry

   32 citations · 2022
2. 2
   Development of Trajectories Through the Kalman Algorithm and Application to an Industrial Robot in the Automotive Industry

   32 citations · 2019

Key Collaborators

Contact & Links