Control de movimiento de un robot humanoide por medio de visión de máquina y réplica de movimientos humanos
Motion control of a humanoid robot through machine vision and human motion replica
Date
2013-12-31
2013-12-31
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Citar con el siguiente link: http://hdl.handle.net/11323/2634
https://revistascientificas.cuc.edu.co/ingecuc/article/view/5
Citar con el siguiente link: http://hdl.handle.net/11323/2634
https://revistascientificas.cuc.edu.co/ingecuc/article/view/5
Abstract
En este artículo se presenta el desarrollo e implementación de un sistema de captura de movimiento antropomórfico mediante técnicas de visión de máquina basado en el dispositivo Kinect, con el fin de realizar el control de movimiento imitativo de un agente robótico Bioloid en el Grupo de Aplicaciones Virtuales (GAV) del Programa de Ingeniería en Mecatrónica de la Universidad Militar Nueva Granada (UMNG). Dados los múltiples grados de libertad de un brazo humano, se busca simplificar una interfaz de control que permita replicar los movimientos de este en un robot humanoide. En este artículo se presentan las técnicas usadas para mejorar el nivel de precisión de los datos entregados por el Kinect y los métodos personalizados de transmisión y codificación de las órdenes enviadas al robot. Los resultados obtenidos derivan en un sistema que cumple con las exigencias básicas de estabilidad, precisión y velocidad de repuesta en la imitación
Referencias:
[1] C.I. Penaloza,Y. Mae, K. Ohara, and T. Arai, “Social human behavior modeling for robot imitation learning”, Mechatronics and Automation (ICMA), 2012 International Conference on , vol., no. , pp. 457-462, Aug. 5 8 2012. [2] S. Hak, N. Mansard, O. Ramos, L. Saab, and O.Stasse, “Capture, recognition and imitation of anthropomorphic motion”, Robotics and Automation (ICRA), 2012 IEEE International Conference on , vol., no., pp. 3539-3540, May. 14 18 2012. [3] Hsien-I Lin, Yu-Cheng Liu, and Chi-Li Chen, “Evaluation of human-robot arm movement imitation”, Control Conference (ASCC), 2011 8th Asian , vol., no., pp. 287- 292, May. 15 18 2011. [4] J. Koenemann and M. Bennewitz, “Whole-body imitation of human motions with a Nao humanoid”, Human- Robot Interaction (HRI), 2012 7th ACM/IEEE International Conference on , vol., no., pp. 425, March. 5 8 2012. [5] J. Smisek, M. Jancosek, and T. Pajdla, “3D with Kinect”, Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on, vol., no., pp.1154- 1160, Nov. 6 13 2011. [6] J. Ekelmann and B. Butka, “Kinect controlled electromechanical skeleton”, Southeastcon, 2012 Proceedings of IEEE , vol., no., pp.1-5, March. 5 18 2012. [7] R. A. El-laithy, J. Huang, and M. Yeh, “Study on the use of Microsoft Kinect for robotics applications”, Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION , vol., no., pp.1280-1288, April 23 26 2012. [8] J. Sung, C. Ponce, B. Selman, and A. Saxena, “Unstructured human activity detection from RGBD images”, Robotics and Automation (ICRA), 2012 IEEE International Conference on , vol., no., pp. 842-849, May. 14 18 2012. [9] A. Bigdelou, T. Benz, L. Schwarz, and N.Navab, “Simultaneous categorical and spatio-temporal 3D gestures using Kinect” 3D User Interfaces (3DUI), 2012 IEEE Symposium on , vol., no., pp.53-60, March. 4 5 2012. [10] I. I. Itauma, H. Kivrak, and H. Kose, “Gesture imitation using machine learning techniques”, Signal Processing and Communications Applications Conference (SIU), 2012 20th , vol., no., pp.1-4, April 18 20 2012. [11] E. Machida, Meifen Cao, T. Murao, and H. Hashimoto, “Human motion tracking of mobile robot with Kinect 3D sensor”, SICE Annual Conference (SICE), 2012 Proceedings of , vol., no., pp. 2207-2211, Aug. 20 23 2012. [12] R. Jimenez, O. Aviles, and F. Espinosa, “Level measurement comparison between 3D vision system based on Kinect and ultrasonic industrial sensor”, in Pakistán Asian Transactions On Engineering, vol. 2, fasc.5, pp.10 - 19, 2012. [13] M. A. Livingston, J. Sebastian, Z. Ai, and J. W. Decker, “Performance measurements for the Microsoft Kinect skeleton”, Virtual Reality Short Papers and Posters (VRW), 2012 IEEE , vol., no., pp.119-120, March. 4 8 2012. [14] Skeletal Joint Smoothing White Paper. Available: http://msdn.microsoft.com/en-us/library/jj131429.aspx#ID4EWPAE. [Fecha de consulta: noviembre de 2012]. [15] Joint Filtering. Available: http://msdn.microsoft.com/enus/library/jj131024.aspx. [Fecha de consulta: noviembre de 2012]
[1] C.I. Penaloza,Y. Mae, K. Ohara, and T. Arai, “Social human behavior modeling for robot imitation learning”, Mechatronics and Automation (ICMA), 2012 International Conference on , vol., no. , pp. 457-462, Aug. 5 8 2012. [2] S. Hak, N. Mansard, O. Ramos, L. Saab, and O.Stasse, “Capture, recognition and imitation of anthropomorphic motion”, Robotics and Automation (ICRA), 2012 IEEE International Conference on , vol., no., pp. 3539-3540, May. 14 18 2012. [3] Hsien-I Lin, Yu-Cheng Liu, and Chi-Li Chen, “Evaluation of human-robot arm movement imitation”, Control Conference (ASCC), 2011 8th Asian , vol., no., pp. 287- 292, May. 15 18 2011. [4] J. Koenemann and M. Bennewitz, “Whole-body imitation of human motions with a Nao humanoid”, Human- Robot Interaction (HRI), 2012 7th ACM/IEEE International Conference on , vol., no., pp. 425, March. 5 8 2012. [5] J. Smisek, M. Jancosek, and T. Pajdla, “3D with Kinect”, Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on, vol., no., pp.1154- 1160, Nov. 6 13 2011. [6] J. Ekelmann and B. Butka, “Kinect controlled electromechanical skeleton”, Southeastcon, 2012 Proceedings of IEEE , vol., no., pp.1-5, March. 5 18 2012. [7] R. A. El-laithy, J. Huang, and M. Yeh, “Study on the use of Microsoft Kinect for robotics applications”, Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION , vol., no., pp.1280-1288, April 23 26 2012. [8] J. Sung, C. Ponce, B. Selman, and A. Saxena, “Unstructured human activity detection from RGBD images”, Robotics and Automation (ICRA), 2012 IEEE International Conference on , vol., no., pp. 842-849, May. 14 18 2012. [9] A. Bigdelou, T. Benz, L. Schwarz, and N.Navab, “Simultaneous categorical and spatio-temporal 3D gestures using Kinect” 3D User Interfaces (3DUI), 2012 IEEE Symposium on , vol., no., pp.53-60, March. 4 5 2012. [10] I. I. Itauma, H. Kivrak, and H. Kose, “Gesture imitation using machine learning techniques”, Signal Processing and Communications Applications Conference (SIU), 2012 20th , vol., no., pp.1-4, April 18 20 2012. [11] E. Machida, Meifen Cao, T. Murao, and H. Hashimoto, “Human motion tracking of mobile robot with Kinect 3D sensor”, SICE Annual Conference (SICE), 2012 Proceedings of , vol., no., pp. 2207-2211, Aug. 20 23 2012. [12] R. Jimenez, O. Aviles, and F. Espinosa, “Level measurement comparison between 3D vision system based on Kinect and ultrasonic industrial sensor”, in Pakistán Asian Transactions On Engineering, vol. 2, fasc.5, pp.10 - 19, 2012. [13] M. A. Livingston, J. Sebastian, Z. Ai, and J. W. Decker, “Performance measurements for the Microsoft Kinect skeleton”, Virtual Reality Short Papers and Posters (VRW), 2012 IEEE , vol., no., pp.119-120, March. 4 8 2012. [14] Skeletal Joint Smoothing White Paper. Available: http://msdn.microsoft.com/en-us/library/jj131429.aspx#ID4EWPAE. [Fecha de consulta: noviembre de 2012]. [15] Joint Filtering. Available: http://msdn.microsoft.com/enus/library/jj131024.aspx. [Fecha de consulta: noviembre de 2012]
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