Konrad Schenk

Papers

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About

Konrad Schenk’s research centers on laser-based and vision-driven perception systems for mobile robotics and human-robot interaction. His most influential work, “Automatic calibration of a stationary network of laser range finders by matching movement trajectories” (2012, 15 citations), addresses a critical challenge in deploying multiple laser range finders (LRFs) for person tracking in large spaces. By enabling automatic calibration through movement trajectory matching, Schenk’s method eliminates manual setup, making multi-LRF networks practical for real-world surveillance and robotics applications. This contribution is foundational for scalable, non-intrusive observation systems. In parallel, his paper “Vision-based hyper-real-time object tracker for robotic applications” (2012, 9 citations) introduces a sparse template-based feature set for ultra-fast visual tracking. This approach prioritizes computational efficiency without sacrificing robustness, enabling real-time object and person tracking essential for dynamic human-robot interaction. Together, these works demonstrate Schenk’s dual focus on practical calibration and high-speed perception. His innovations support safer, more responsive robotic systems in shared environments, and his citation record reflects their utility in advancing autonomous navigation and interactive robotics.