Alexander Braun
Papers
2
Total Citations
13
H-Index
2
About
Alexander Braun is a leading researcher at the intersection of robotics, building information modeling (BIM), and lifelong indoor navigation. His work focuses on developing robust localization and mapping systems that leverage BIM models as prior knowledge for autonomous robots operating in complex, changing built environments. Braun’s major contributions include pioneering the integration of BIM with simultaneous localization and mapping (SLAM) and particle filter-based localization, addressing the critical challenge of Scan-BIM deviations—the discrepancies between as-designed models and real-world conditions. His highly cited paper "BIM-SLAM: Integrating BIM Models in Multi-session SLAM for Lifelong Mapping using 3D LiDAR" (8 citations) introduces a framework for persistent, adaptive mapping, while "OGM2PGBM: Robust BIM-based 2D-LiDAR localization for lifelong indoor navigation" (5 citations) proposes a method resilient to model-reality mismatches. These works are foundational for enabling reliable, long-term robot autonomy in facilities management, construction monitoring, and smart building applications. Braun’s research bridges digital twins and field robotics, offering practical solutions for the AEC industry’s digitalization. His achievements are shaping the future of indoor navigation, making him a key voice in the growing field of BIM-driven robotics.
Research Focus
Key Achievements
Top Papers
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