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Research Article
Facial Movement Based Robotic Arm Control Using Arduino and Python
Dr.S.Ramesh1
Mohammed Al Fahad2
Prem Prakash S3
Kavinraj V4
Deepa V5
1Head of the Department, Professor, Electrical and Electronics Engineering, K.S.R College of Engineering, Tiruchengode, Tamil Nadu, India. 2,3,4,5 Electrical and Electronics Engineering, K.S.R College of Engineering, Tiruchengode , Tamil Nadu, India
Published Online: January-February 2023
Pages: 151-154
Cite this article
No DOIReferences
1. Agarwal, A., JeevithaShree, D. V., Saluja, K. S., Sahay, A., Mounika, P., Sahu, A. & Biswas, P. (2019). Comparing Two Webcam-Based
Eye Gaze Trackers for Users with Severe Speech and Motor Impairment. In Research into Design for a Connected World (pp. 641-652).
Springer, Singapore.
2. Alsharif S., Kuzmicheva O. and Gräser A. (2016), Gaze Gesture-Based Human Robot Interface, Zweite transdisziplinäre
Konferenz,Technische Unterstützungssysteme, die Menschen wirklich wollen, 2016
3. Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L. P. (2018). Openface 2.0: Facial behavior analysis toolkit. In 2018 13th IEEE
International Conference on Automatic Face & Gesture Recognition (FG 2018) (pp. 59-66). IEEE.
4. Bannat, A., Gast, J., Rehrl, T., Rösel, W., Rigoll, G., & Wallhoff, F. (2009). A multimodal human-robot-interaction scenario: Working
together with an industrial robot. In International Conference on Human-Computer Interaction (pp. 303-311). Springer, Berlin,
Heidelberg.
5. Betke, Margrit, James Gips, and Peter Fleming (2002) "The camera mouse: visual tracking of body features to provide computer access
for people with severe disabilities." IEEE Transactions on neural systems and Rehabilitation Engineering 10.1: 1-10.
6. Biswas P. and Jeevithashree DV (2018), Eye Gaze Controlled MFD for Military Aviation, ACM International Conference on Intelligent
User Interfaces (IUI) 2018
7. Bonneau, E., Taha, F., Gravez, P., & Lamy, S. (2004). Surgicobot: Surgical gesture assistance cobot for maxillo-facial interventions. In
Perspective in Image-Guided Surgery(pp. 353-360).
8. Bremner, P., Celiktutan, O., & Gunes, H. (2016). Personality perception of robot avatar teleoperators. In 2016 11th ACM/IEEE
International Conference on Human-Robot Interaction (HRI) (pp. 141-148). IEEE
9. Chen Y. and Newman W. S. (2004), A Human-Robot Interface Based on Electrooculography, Proceedings of the IEEE Intl Conf on
Robotics and Automation
10. Dautenhahn, K., Woods, S., Kaouri, C., Walters, M. L., Koay, K. L., & Werry, I. (2005). What is a robot companion-friend, assistant or
butler?. In 2005 IEEE/RSJ international conference on intelligent robots and systems (pp. 1192-1197). IEEE.
11. Fitts P.M. (1954), The Information Capacity of the Human Motor System In Controlling The Amplitude of Movement, Journal of
Experimental Psychology 47 (1954): 381-391
12. Hansen, J. P., Alapetite, A., MacKenzie, I. S., & Møllenbach, E. (2014). The use of gaze to control drones. In Proceedings of the
Symposium on Eye Tracking Research and Applications (pp. 27-34)
13. Rosebrock A. (2019), Facial landmarks with dlib, OpenCV, and Python, Available at https://www.pyimagesearch.com/2017/04/03/faciallandmarks-dlib-opencv-python/
14. San Agustin, J., Skovsgaard, H., Mollenbach, E., Barret, M., Tall, M., Hansen, D. W., & Hansen, J. P. (2010). Evaluatiion of a low-cost
open-source gaze tracker. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications 77-80.
15. Dostal, J., Kristensson, P. O., & Quigley, A. (2013). Subtle gaze-dependent techniques for visualising display changes in multi-display
environments. In Proceedings of the 2013 international conference on Intelligent user interfaces (pp. 137-148). ACM.
16. Dziemian, Sabine, William W. Abbott, and A. Aldo Faisal (2016), Gaze-based teleprosthetic enables intuitive continuous control of
complex robot arm use: Writing & drawing. 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics
(BioRob). IEEE, 2016.
17. Jeevithashree, D. V., Saluja, K. S., & Biswas, P. (2019). A case study of developing gaze controlled interface for users with severe
speech and motor impairment. Technology and Disability, 31(1-2), 63-76.
18. Kim, D. H., Kim, J. H., Yoo, D. H., Lee, Y. J., & Chung, M. J. (2001). A human-robot interface using eye-gaze tracking system for people
with motor disabilities. Transaction on Control, Automation and Systems Engineering, 3(4), 229-235.
19. Koch, P. J., van Amstel, M. K., Dębska, P., Thormann, M. A., Tetzlaff, A. J., Bøgh, S., & Chrysostomou, D. (2017). A skill-based robot
co-worker for industrial maintenance tasks. Procedia Manufacturing, 11, 83-90.
20. Khonglah, J. R., & Khosla, A. (2015). A low cost webcam based eye tracker for communicating through the eyes of young children with
ASD. In Next Generation Computing Technologies (NGCT), 2015 1st IEEE International Conference on 925-928.
Eye Gaze Trackers for Users with Severe Speech and Motor Impairment. In Research into Design for a Connected World (pp. 641-652).
Springer, Singapore.
2. Alsharif S., Kuzmicheva O. and Gräser A. (2016), Gaze Gesture-Based Human Robot Interface, Zweite transdisziplinäre
Konferenz,Technische Unterstützungssysteme, die Menschen wirklich wollen, 2016
3. Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L. P. (2018). Openface 2.0: Facial behavior analysis toolkit. In 2018 13th IEEE
International Conference on Automatic Face & Gesture Recognition (FG 2018) (pp. 59-66). IEEE.
4. Bannat, A., Gast, J., Rehrl, T., Rösel, W., Rigoll, G., & Wallhoff, F. (2009). A multimodal human-robot-interaction scenario: Working
together with an industrial robot. In International Conference on Human-Computer Interaction (pp. 303-311). Springer, Berlin,
Heidelberg.
5. Betke, Margrit, James Gips, and Peter Fleming (2002) "The camera mouse: visual tracking of body features to provide computer access
for people with severe disabilities." IEEE Transactions on neural systems and Rehabilitation Engineering 10.1: 1-10.
6. Biswas P. and Jeevithashree DV (2018), Eye Gaze Controlled MFD for Military Aviation, ACM International Conference on Intelligent
User Interfaces (IUI) 2018
7. Bonneau, E., Taha, F., Gravez, P., & Lamy, S. (2004). Surgicobot: Surgical gesture assistance cobot for maxillo-facial interventions. In
Perspective in Image-Guided Surgery(pp. 353-360).
8. Bremner, P., Celiktutan, O., & Gunes, H. (2016). Personality perception of robot avatar teleoperators. In 2016 11th ACM/IEEE
International Conference on Human-Robot Interaction (HRI) (pp. 141-148). IEEE
9. Chen Y. and Newman W. S. (2004), A Human-Robot Interface Based on Electrooculography, Proceedings of the IEEE Intl Conf on
Robotics and Automation
10. Dautenhahn, K., Woods, S., Kaouri, C., Walters, M. L., Koay, K. L., & Werry, I. (2005). What is a robot companion-friend, assistant or
butler?. In 2005 IEEE/RSJ international conference on intelligent robots and systems (pp. 1192-1197). IEEE.
11. Fitts P.M. (1954), The Information Capacity of the Human Motor System In Controlling The Amplitude of Movement, Journal of
Experimental Psychology 47 (1954): 381-391
12. Hansen, J. P., Alapetite, A., MacKenzie, I. S., & Møllenbach, E. (2014). The use of gaze to control drones. In Proceedings of the
Symposium on Eye Tracking Research and Applications (pp. 27-34)
13. Rosebrock A. (2019), Facial landmarks with dlib, OpenCV, and Python, Available at https://www.pyimagesearch.com/2017/04/03/faciallandmarks-dlib-opencv-python/
14. San Agustin, J., Skovsgaard, H., Mollenbach, E., Barret, M., Tall, M., Hansen, D. W., & Hansen, J. P. (2010). Evaluatiion of a low-cost
open-source gaze tracker. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications 77-80.
15. Dostal, J., Kristensson, P. O., & Quigley, A. (2013). Subtle gaze-dependent techniques for visualising display changes in multi-display
environments. In Proceedings of the 2013 international conference on Intelligent user interfaces (pp. 137-148). ACM.
16. Dziemian, Sabine, William W. Abbott, and A. Aldo Faisal (2016), Gaze-based teleprosthetic enables intuitive continuous control of
complex robot arm use: Writing & drawing. 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics
(BioRob). IEEE, 2016.
17. Jeevithashree, D. V., Saluja, K. S., & Biswas, P. (2019). A case study of developing gaze controlled interface for users with severe
speech and motor impairment. Technology and Disability, 31(1-2), 63-76.
18. Kim, D. H., Kim, J. H., Yoo, D. H., Lee, Y. J., & Chung, M. J. (2001). A human-robot interface using eye-gaze tracking system for people
with motor disabilities. Transaction on Control, Automation and Systems Engineering, 3(4), 229-235.
19. Koch, P. J., van Amstel, M. K., Dębska, P., Thormann, M. A., Tetzlaff, A. J., Bøgh, S., & Chrysostomou, D. (2017). A skill-based robot
co-worker for industrial maintenance tasks. Procedia Manufacturing, 11, 83-90.
20. Khonglah, J. R., & Khosla, A. (2015). A low cost webcam based eye tracker for communicating through the eyes of young children with
ASD. In Next Generation Computing Technologies (NGCT), 2015 1st IEEE International Conference on 925-928.
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