Papers
27
Total Citations
396
H-Index
9
About
Klaus Diepold is a leading researcher at the intersection of cognitive systems, robotics, and auditory perception. His work fundamentally advances how machines perceive and interact with their environment, with a particular focus on binaural 3D sound localization—a technique that mimics human hearing to enable robots to pinpoint sound sources in real time using just two microphones. His 2006 paper on HRTF-based localization (50 citations) and its enhanced algorithm (37 citations) laid the groundwork for robotic hearing in surveillance and humanoid applications. Beyond audition, Diepold has made pivotal contributions to cognitive production systems, as evidenced by his most-cited work, "Artificial Cognition in Production Systems" (127 citations), which explores how manufacturing can become flexible and autonomous. He has also tackled computer vision, notably with a robust solution to the five-point relative pose problem (15 citations), and human-robot interaction, studying autonomy's impact on user experience (15 citations). His cognitive system for autonomous robotic welding (14 citations) exemplifies his drive to integrate learning and perception into industrial practice. With over 300 total citations across these diverse areas, Diepold's research continues to shape the future of intelligent, perceptive machines.
Research Focus
Key Achievements
Top Papers
- 1Artificial Cognition in Production Systems127 citations · 2010
- 2A New Method for Binaural 3-D Localization Based on Hrtfs50 citations · 2006
- 3An Enhanced Binaural 3D Sound Localization Algorithm37 citations · 2006
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- 6High performance 3D sound localization for surveillance applications15 citations · 2007
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- 8A cognitive system for autonomous robotic welding14 citations · 2009
- 9Evaluation of a RGB-LED-based Emotion Display for Affective Agents11 citations · 2016
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