Miguel Arturo Vega Torres
Papers
2
Total Citations
13
H-Index
2
About
Miguel Arturo Vega Torres is a leading researcher at the intersection of robotics, computer vision, and the Architecture, Engineering, and Construction (AEC) industry. His work focuses on solving the critical challenge of lifelong, robust indoor navigation by integrating Building Information Models (BIM) with Simultaneous Localization and Mapping (SLAM). Vega Torres’s major contribution is the development of novel frameworks that bridge the gap between static digital models and dynamic real-world environments. His paper “BIM-SLAM: Integrating BIM Models in Multi-session SLAM for Lifelong Mapping using 3D LiDAR” (2023, 8 citations) pioneers a method for creating persistent, updatable maps by fusing prior BIM knowledge with live sensor data. Addressing a key limitation of prior work, his paper “OGM2PGBM: Robust BIM-based 2D-LiDAR localization for lifelong indoor navigation” (2023, 5 citations) introduces a robust particle filter algorithm that explicitly handles Scan-BIM deviations—the inevitable discrepancies between a reference model and the actual built space. This work is foundational for enabling autonomous robots to navigate reliably in complex, changing indoor environments over extended periods, with direct applications in facility management, construction monitoring, and service robotics.
Research Focus
Key Achievements
Top Papers
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