Dyah Anggraeni
Papers
10
Total Citations
161
H-Index
7
About
Dyah Anggraeni is a researcher at the forefront of human-robot interaction and intelligent control systems, with a particular focus on making robotics more accessible through natural interfaces. Her work spans speech recognition, computer vision, and assistive technologies, and she is best known for developing methods that allow robots to understand and respond to human commands. Her most impactful contributions include the implementation of speech recognition for robot arm control using Mel-Frequency Cepstrum Coefficients (MFCC) combined with Support Vector Machines (SVM) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which have together garnered over 75 citations. She also pioneered the development of SyPEHUL, a social robot capable of real-time face recognition and tracking using Cascade Classification and LBPH, as well as expression recognition for more natural human-robot interaction. Beyond robotics, Anggraeni has applied her technical expertise to create assistive tools like the Q-Bot Ver3, a real-time Qibla finder and prayer time device, and an Electrooculogram (EOG) system for controlling mobile robots via eye movements. Her work demonstrates a consistent commitment to bridging the gap between complex machine learning algorithms and practical, user-friendly robotic applications.
Research Focus
Key Achievements
Top Papers
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- 3The design of face recognition and tracking for human-robot interaction26 citations · 2017
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