Urban B. Himmelsbach
Papers
6
Total Citations
61
H-Index
4
About
Urban B. Himmelsbach is a leading researcher in human-robot collaboration (HRC), focusing on making industrial and medical robots safer and more efficient through advanced sensing and differentiation technologies. His major contributions center on developing speed and separation monitoring systems using 3D time-of-flight cameras and single-pixel sensors, enabling robots to detect obstacles and distinguish humans from non-human objects in real time. His most cited work, "Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration" (2021, 20 citations), demonstrates how thermal imaging and convolutional neural networks can boost collaborative application performance. Himmelsbach’s research addresses critical gaps in ISO/TS 15066 compliance, particularly for gripper-integrated 360-degree separation monitoring and medical applications, where his 2017 paper pioneered wireless connectivity for obstacle detection. With over 60 total citations across six key papers, his work has directly influenced the design of safer, more efficient collaborative robots. Notably, his 2023 study on classifying thermal images with CNNs represents a novel approach to human-machine differentiation, promising to enhance productivity without compromising safety.
Research Focus
Key Achievements
Top Papers
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