Raquel Pacheco

Papers

Total Citations

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About

Raquel Pacheco is a robotics researcher whose work centers on advancing safe human-robot collaboration and vision-based automation for industrial applications. Her primary contributions lie in developing reliable perception systems and skill-based programming frameworks that enable robots to operate flexibly and safely alongside humans. Her most cited paper, "Reliable Workspace Monitoring in Safe Human-Robot Environment" (2016, 6 citations), addresses a critical challenge in collaborative production: implementing a robust vision system for full environmental perception, allowing robots to adapt to frequently changing tasks without compromising worker safety. In her related work, "Skills for vision-based applications in robotics application to aeronautics assembly pilot station" (2015, 4 citations), Pacheco introduces an innovative approach that organizes complex computer vision problems into reusable "skills," simplifying the deployment of vision-guided robots in specialized settings like aeronautics assembly. This skill-based methodology reduces the need for custom programming, making robotic systems more accessible and efficient for industry. Though her citation counts reflect a focused, early-career impact, Pacheco’s research is foundational for the next generation of flexible, safe, and intelligent manufacturing environments.