Freek De Bruijn

Papers

Total Citations

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About

Freek De Bruijn’s research lies at the intersection of robotics, non-destructive testing, and probabilistic mapping, with a focus on infrastructure inspection and structural health monitoring. His most cited work introduces a Bayesian fusion framework for generating probabilistic pipe thickness maps, drawing direct parallels to 2.5D elevation maps in robotics—a novel cross-disciplinary approach that bridges robotic perception with industrial condition assessment. This paper has garnered 24 citations, establishing a foundation for uncertainty-aware inspection in pipelines. De Bruijn also contributed to urban search and rescue robotics, addressing the critical challenge of planning stable paths for robots navigating rubble and debris. His work on robot-assisted inspection of concrete box girders in bridges demonstrates a practical, multi-sensor system combining laser range finders, RGB-D cameras, and inertial measurement units on a tracked platform, enabling safe internal bridge inspections. While his citation counts reflect a focused, early-career impact, De Bruijn’s contributions are notable for their direct translation of robotic mapping and planning techniques to real-world civil infrastructure challenges, offering a template for future autonomous inspection systems.