Öz
It is obvious that the medical, military and industry are the sectors
which mostly benefit from the technological developments. Innovations and
improvements about robotic technology find place in these listed sectors
directly or indirectly. For example, in a medical application; touches of the
robotic fingers can be sensed by human through electrodes which are located
into the brain. In military field, vehicles with robotic arm can do
searching/destruction activities in dangerous areas. On the other hand, in
industrial field robotic arm technology is used in manufactural activities
frequently. In this practical application, it is purposed that sensing of
motions and carrying over to the robotic arm without auxiliary instrument apart
from the Leap MotionTM Controller (LMC). In this way, an application that imitates human arm and hand motions
has been developed. This study has specific features which can be used for
various purposes in medical, military and industrial fields. Furthermore, it
contributes an innovative approach to operator-assisted robotic arm technology.
Anahtar Kelimeler
Operator-assisted Robotic arm Leap Motion Controller Innovation
Kaynakça
- Chen, Z. H., Kim, J. T., Liang, J., Zhang, J., and Yuan, Y. B. (2014). Real-time hand gesture recognition using finger segmentation. The Scientific World Journal, Vol. 2014, 1-9.
- Dan, R. B., and Mohod, P. S. (2014). Survey on Hand Gesture Recognition Approaches. International Journal of Computer Science and Information Technologies, Vol. 5(2) 2050-2052.
- Garcia, E., Jimenez, M. A., De Santos, P. G., and Armada, M. (2007). The evolution of robotics research. IEEE Robotics & Automation Magazine, 14(1), 90-103.
- Garg, P., Aggarwal, N., and Sofat, S. (2009). Vision based hand gesture recognition. World Academy of Science, Engineering and Technology, 49(1), 972-977.
- Iwai, Y., Watanabe, K., Yagi, Y., and Yachida, M. (1996). Gesture recognition by using colored gloves. In Systems, Man, and Cybernetics, IEEE International Conference on (Vol. 1, pp. 76-81). IEEE.
- Khan, R. Z., and Ibraheem, N. A. (2012). Hand gesture recognition: a literature review. International journal of artificial Intelligence & Applications, 3(4), 161-174.
- Kumar, P., Verma, J., and Prasad, S. (2012). Hand data glove: a wearable real-time device for human-computer interaction. International Journal of Advanced Science and Technology, 43, 15-25.
- Marin, G., Dominio, F., and Zanuttigh, P. (2014, October). Hand gesture recognition with leap motion and kinect devices. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 1565-1569). IEEE.
- Nadarajan, G. (2005). Islamic Automation: A Reading of al-Jazari's The Book of Knowledge of Ingenious Mechanical Devices (1206).
- Petrina, A. M. (2011). Advances in robotics (Review). Automatic documentation and mathematical linguistics, 45(2), 43-57.
Öz
It is obvious that the medical, military and industry are the sectors
which mostly benefit from the technological developments. Innovations and
improvements about robotic technology find place in these listed sectors
directly or indirectly. For example, in a medical application; touches of the
robotic fingers can be sensed by human through electrodes which are located
into the brain. In military field, vehicles with robotic arm can do
searching/destruction activities in dangerous areas. On the other hand, in
industrial field robotic arm technology is used in manufactural activities
frequently. In this practical application, it is purposed that sensing of
motions and carrying over to the robotic arm without auxiliary instrument apart
from the Leap MotionTM Controller (LMC). In this way, an application that imitates human arm and hand motions
has been developed. This study has specific features which can be used for
various purposes in medical, military and industrial fields. Furthermore, it
contributes an innovative approach to operator-assisted robotic arm technology.
Anahtar Kelimeler
Kaynakça
- Chen, Z. H., Kim, J. T., Liang, J., Zhang, J., and Yuan, Y. B. (2014). Real-time hand gesture recognition using finger segmentation. The Scientific World Journal, Vol. 2014, 1-9.
- Dan, R. B., and Mohod, P. S. (2014). Survey on Hand Gesture Recognition Approaches. International Journal of Computer Science and Information Technologies, Vol. 5(2) 2050-2052.
- Garcia, E., Jimenez, M. A., De Santos, P. G., and Armada, M. (2007). The evolution of robotics research. IEEE Robotics & Automation Magazine, 14(1), 90-103.
- Garg, P., Aggarwal, N., and Sofat, S. (2009). Vision based hand gesture recognition. World Academy of Science, Engineering and Technology, 49(1), 972-977.
- Iwai, Y., Watanabe, K., Yagi, Y., and Yachida, M. (1996). Gesture recognition by using colored gloves. In Systems, Man, and Cybernetics, IEEE International Conference on (Vol. 1, pp. 76-81). IEEE.
- Khan, R. Z., and Ibraheem, N. A. (2012). Hand gesture recognition: a literature review. International journal of artificial Intelligence & Applications, 3(4), 161-174.
- Kumar, P., Verma, J., and Prasad, S. (2012). Hand data glove: a wearable real-time device for human-computer interaction. International Journal of Advanced Science and Technology, 43, 15-25.
- Marin, G., Dominio, F., and Zanuttigh, P. (2014, October). Hand gesture recognition with leap motion and kinect devices. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 1565-1569). IEEE.
- Nadarajan, G. (2005). Islamic Automation: A Reading of al-Jazari's The Book of Knowledge of Ingenious Mechanical Devices (1206).
- Petrina, A. M. (2011). Advances in robotics (Review). Automatic documentation and mathematical linguistics, 45(2), 43-57.
Ayrıntılar
| Konular | Mühendislik |
|---|---|
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 31 Ekim 2017 |
| Gönderilme Tarihi | 4 Nisan 2017 |
| Yayımlandığı Sayı | Yıl 2017 Cilt: 7 Sayı: 1 |
