Corneliu Rusu
Papers
11
Total Citations
80
H-Index
6
About
Corneliu Rusu is a leading researcher in audio signal processing for service robotics, with a focus on enabling robots to understand and respond to their acoustic environment. His major contributions center on extending the auditory capabilities of the TIAGo service robot, developing algorithms for sound classification, context awareness, and real-time warning systems that allow robots to integrate seamlessly into everyday life and healthcare settings. Rusu’s work has produced a comprehensive audio database of over 3,300 signals for training and evaluation, and his classification systems—using Mel-frequency cepstral coefficients and nearest-neighbor methods—have achieved over 99% accuracy in recognizing indoor human activities. His papers have garnered significant attention, with his most cited work, “Adding audio capabilities to TIAGo service robot” (2018), accumulating 18 citations, and his research on emotion recognition and deep learning-based classification pushing the boundaries of human-robot interaction. Rusu’s innovative approach to acoustic monitoring and his development of Romanian-language audio datasets for service robots underscore his impact on making robots more responsive and helpful in assisted living environments.
Research Focus
Key Achievements
Top Papers
- 1Adding audio capabilities to TIAGo service robot18 citations · 2018
- 2Extending Assisted Audio Capabilities of TIAGo Service Robot14 citations · 2019
- 3Recent developments in acoustical signal classification for monitoring10 citations · 2017
- 4Audio Database for TIAGo Service Robot7 citations · 2021
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- 6Sound Classification Algorithms for Indoor Human Activities7 citations · 2021
- 7A Real-Time Warning Based on TIAGo's Audio Capabilities4 citations · 2022
- 8Emotion Recognition Audio Database for Service Robots4 citations · 2022
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