Papers
16
Total Citations
290
H-Index
10
About
Samuel A. Prieto is a pioneering researcher at the intersection of robotics, autonomous systems, and the built environment, with a body of work that has fundamentally advanced how buildings are digitized, inspected, and monitored. His research spans autonomous indoor navigation, semantic 3D reconstruction, and the integration of robotic systems into construction workflows — areas where he has established himself as a leading voice. Prieto's most celebrated contribution, an autonomous robotic platform for extracting detailed semantic building models (2019, 59 citations), demonstrated that robots could intelligently interpret and reconstruct architectural spaces with minimal human input. Complementing this, his probabilistic next best scan approach (2017, 44 citations) offered a sophisticated solution to the long-standing challenge of efficient, complete indoor mapping. His earlier foundational work on automatic indoor scanning with mobile robots (2015, 32 citations) laid the conceptual groundwork for much of this field. Beyond reconstruction, Prieto has tackled practical construction-industry challenges, developing methodologies for automated construction progress monitoring and quality inspection systems like AutoCIS. His 2024 practitioner's guide to robotic integration reflects a commitment to bridging academic research and real-world application. With over 260 cumulative citations, his influence continues to grow as robotics transforms the construction industry.
Research Focus
Key Achievements
Top Papers
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- 3Towards the Automatic Scanning of Indoors with Robots32 citations · 2015
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- 5Door detection in 3D colored laser scans for autonomous indoor navigation26 citations · 2016
- 6A Methodology to Monitor Construction Progress Using Autonomous Robots18 citations · 2020
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- 10Passing through Open/Closed Doors: A Solution for 3D Scanning Robots12 citations · 2019