TY - GEN
T1 - Application of Convolutional Neural Networks to Emotion Recognition for Robotic Arm Manipulation
AU - Fuertes, Walter
AU - Hunter, Karen
AU - Benitez, Diego S.
AU - Perez, Noel
AU - Grijalva, Felipe
AU - Baldeon-Calisto, Maria
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/7/26
Y1 - 2023/7/26
N2 - This paper presents the development of a system that operates a robotic arm to deliver an object based on the facial expression of a human standing in front of the robot, demonstrating real-Time emotion recognition for physical Human-Robot Interaction. To achieve this, a convolutional neural network-based model was developed to identify emotions in real time. The robotic arm operation was implemented using an embedded NVidia Jetson Nano computer, a web camera, and OpenCV, ROS, and TensorFlow libraries. Using a 26.6k face photos data set from the emotion detection database, the built emotion detection model demonstrated an accuracy of 93.5% and an error of 6.5% during training and validation. The final real-Time prototype had a testing accuracy of 94% with an error of 6%. This proof-of-concept shows that in the near future more advanced applications that harness user emotions may also be built.
AB - This paper presents the development of a system that operates a robotic arm to deliver an object based on the facial expression of a human standing in front of the robot, demonstrating real-Time emotion recognition for physical Human-Robot Interaction. To achieve this, a convolutional neural network-based model was developed to identify emotions in real time. The robotic arm operation was implemented using an embedded NVidia Jetson Nano computer, a web camera, and OpenCV, ROS, and TensorFlow libraries. Using a 26.6k face photos data set from the emotion detection database, the built emotion detection model demonstrated an accuracy of 93.5% and an error of 6.5% during training and validation. The final real-Time prototype had a testing accuracy of 94% with an error of 6%. This proof-of-concept shows that in the near future more advanced applications that harness user emotions may also be built.
KW - convolution neural networks
KW - emotion recognition
KW - robotic arm control
UR - https://www.scopus.com/pages/publications/85171613731
U2 - 10.1109/ColCACI59285.2023.10225880
DO - 10.1109/ColCACI59285.2023.10225880
M3 - Contribución a la conferencia
AN - SCOPUS:85171613731
T3 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)
BT - 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Proceedings
A2 - Orjuela-Canon, Alvaro David
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023
Y2 - 26 July 2023 through 28 July 2023
ER -