Alexander Heilig

Papers

Total Citations

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About

Alexander Heilig’s research lies at the intersection of industrial and service robotics, with a focus on sensor-driven manipulation and localization. His most cited work, “Tracking, reconstruction and grasping of unknown rotationally symmetrical objects from a conveyor belt” (2017, 14 citations), addresses a critical challenge in automated manufacturing: enabling robots to reliably detect, track, and grasp moving objects without prior geometric models. By integrating intrinsic and extrinsic sensors into a closed control loop, Heilig’s approach enhances real-time adaptability for high-speed industrial environments. In parallel, his 2018 paper on “Adaptive particle filter for localization problem in service robotics” (10 citations) advances probabilistic localization for autonomous systems operating in human-centric spaces. He introduces a novel likelihood computation and adaptive resampling algorithm tailored for low-cost ultrasonic sensors, significantly improving the efficiency of Monte Carlo Localization in cluttered, dynamic settings. Together, these contributions demonstrate Heilig’s ability to bridge theoretical sensor fusion with practical robotic applications, offering scalable solutions for both factory floors and service robots. His work is particularly notable for its emphasis on cost-effective sensing and real-time performance, making advanced robotics more accessible for real-world deployment.