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About

Harald Gietler is a robotics researcher whose work bridges the gap between sensor innovation and real-world automation. His key research areas include electromagnetic pose estimation, angular position sensing, and sensor fusion for robotic manipulation. Gietler’s major contribution is the development of robust, scalable sensing systems that enable precise tracking and automation in challenging environments. His most cited work (15 citations) introduces a wireless electromagnetic field-based sensor for 6-DOF tracking of moving objects like drones, offering a complementary alternative to GPS and vision systems. He also designed a scalable retrofit angular position sensor (6 citations) to equip existing machinery with autonomous capabilities, and applied learning-based visual grasping point prediction to automate forestry crane log-grasping (5 citations). Notably, his simulation work combining AMCW ToF cameras and FMCW radar (2 citations) supports rapid prototyping for sensor fusion frameworks. Gietler’s research stands out for its practical focus on retrofitting and automation, making advanced sensing accessible for industrial and field robotics.