Christian Huemmer
Papers
1
Total Citations
13
H-Index
1
About
Christian Huemmer is a researcher whose work sits at the intersection of acoustic signal processing and robotics, with a particular focus on how machines can better perceive and interpret sound in real-world environments. His key research areas include beamforming, head-related transfer functions (HRTFs), and robust audio processing for robotic platforms. Huemmer’s major contribution lies in the development of an HRTF-based robust least-squares frequency-invariant (RLSFI) beamformer, which accounts for the acoustic shadowing and diffraction effects caused by a robot’s own head. This innovation significantly improves the spatial selectivity and robustness of sound capture in noisy, dynamic settings—a critical capability for human-robot interaction. His most-cited paper, published in 2015, has accumulated 13 citations, reflecting its foundational role in the field. By bridging the gap between theoretical beamforming and practical robotic audition, Huemmer has helped pave the way for more natural and responsive auditory systems in autonomous agents. His work is especially relevant for researchers developing hearing-enabled robots for applications ranging from assistive technology to search-and-rescue operations.
Research Focus
Key Achievements
Top Papers
- 1HRTF-based robust least-squares frequency-invariant beamforming13 citations · 2015