Papers

6

Total Citations

179

H-Index

6

About

Stephen DeVito is an emerging researcher at the forefront of construction robotics and automation, with a focused body of work exploring how quadruped robots can revolutionize construction progress monitoring. His research addresses a critical pain point in the construction industry: the inefficiency, inconsistency, and labor intensity of traditional manual inspection processes. By integrating technologies such as augmented reality, Building Information Modeling (BIM), and autonomous navigation, DeVito and his collaborators have developed sophisticated methodologies that enable real-time, remote, and automated data capture on construction sites. His most cited work, "Real-Time and Remote Construction Progress Monitoring with a Quadruped Robot Using Augmented Reality" (2022, 57 citations), demonstrates how four-legged robots can serve as persistent, accurate inspection agents where human limitations fall short. Complementary studies on BIM-enabled reality capture and autonomous navigation accuracy further establish a comprehensive framework for deploying legged robots in practical construction environments. His contributions to the 2021 ISARC Proceedings (28 citations) also reflect his engagement with the broader automation and robotics research community. With nearly 180 combined citations across six publications, DeVito's work is shaping a new paradigm for intelligent, robot-assisted construction management.

Research Focus

Key Achievements

6
H-Index
6
Papers
179
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time and Remote Construction Progress Monitoring with a Quadruped Robot Using Augmented Reality
57 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 103
🏛 Institutions: China Railway Construction Corporation (China), Link Consulting

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago