David Seidl

Papers

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About

David Seidl is a robotics researcher whose work centers on sensor calibration and 3D simultaneous localization and mapping (SLAM). His most-cited contribution, "Calibration of Short Range 2D Laser Range Finder for 3D SLAM Usage" (2015, 35 citations), addresses a critical bottleneck in mobile robotics: ensuring that affordable short-range laser scanners deliver the accuracy needed for reliable 3D mapping. Seidl developed a systematic calibration procedure that corrects systematic errors in these sensors, enabling their effective use in SLAM systems—a foundational capability for autonomous navigation in indoor and confined environments. This work has been cited by researchers improving sensor fusion and low-cost robotic perception. Beyond this paper, Seidl’s research portfolio spans multi-sensor integration and field robotics, demonstrating a practical, problem-driven approach to making advanced robotics accessible. His calibration method remains a reference for engineers building robust, cost-effective mapping solutions, highlighting his impact on both academic research and real-world robotic applications.