Remote operation of a mobile robot using a smartphone

Main Article Content

Fco. Abiud Rojas de Silva G.
Karla A. Trejo Ramírez

Abstract

This paper presents an approach to remote control a robot using smartphone. The main idea is to collect data generated by the accelerometer sensor included in the smartphone. The data are the results of moving the smartphone in direction of the axis Y and Z. Such data will be used for training two neural networks that will define the direction of the movement of the mobile robot. The outputs obtained from the neural networks will be processed to compute and plot the trajectory, which is determined by the kinematic model for a tricycle mobile robot.

Article Details

Section
Scientific Paper
Author Biography

Carlos Alberto Flores Vázquez

Mi preparación de tercer nivel la realice en el campo de la Ingeniería Electrónica. Adicionalmente, poseo estudios de cuarto nivel, dentro del país un MBA y fuera un Máster en Automática y Robótica.En cuanto a mi experiencia profesional, poseo 4 años en el campo de las automatizaciones, 6 años en cargos administrativos, 7 años en labores docentes y 1 año como investigador.Me defino como una persona receptiva, abierta a solicitar y proporcionar ayuda, con capacidad de adaptación rápida a los cambios, orientado a objetivos, preparado para trabajo bajo presión, consciente de la importancia de la planificación, el trabajo en equipo y delegar tareas.El desarrollo e implementación de soluciones tecnológicas (SCADA, PLC, Microcontroladores, Robótica, Instrumentación, PCB, Inteligencia Artificial, Visión por Computador) para distintos procesos de producción, es una de las fortalezas en mi formación profesional.

References

[1] J. Cui, S. Tosunoglu, R. Roberts, C. Moore, and D. W. Repperger, “A review of teleoperation system control,” in Proceedings of the 2006 Florida conference recente advances in robotics (FCRAR), Florida Atlantic University,FL, 2003.

[2] P. P. Batsomboon, S. Tosunoglu, and D. W. Repperger,“Development of a mechatronic system: a telesensation system for training and teleoperation,” Chapter, Recent Advances in Mechatronics, Springer-Verlag, New York, pp. 304–321, 1999.

[3] H. Hu, L. Yu, P. Wo Tsui, and Q. Zhou, “Internet-based robotic systems for teleoperation,” Assembly Automation, vol. 21, no. 2, pp. 143–152, 2001.

[4] E. Slawinski, V. Mut, and J. Postigo, “Teleoperation of mobile robots,” Latin American applied research, vol. 36, no. 2, pp. 79–86, 2006.

[5] Y. Kimitsuka, T. Suzuki, and K. Sawai, “Development of mobile robot teleoperation system utilizing robot sensor network,” in Networked Sensing Systems, 2008. INSS 2008. 5th International Conference on, pp. 250-250, IEEE, 2008.

[6] A. Uribe, S. Alves, J. M. Rosário, B. Pérez-Gutiérrez, et al., “Mobile robotic teleoperation using gesture based human interfaces,” in Robotics Symposium, 2011 IEEE IX Latin American and IEEE Colombian Conference on Automatic Control and Industry Applications(LARC), pp. 1–6, IEEE, 2011.

[7] H. Surmann, D. Holz, S. Blumental, T. Linder, P. Molitor, and V. Tretyakov, “Teleoperated visual inspection and surveillance with unmanned ground and aerial vehicles.,” iJOE, vol. 4, no. 4, pp. 26–38, 2008.

[8] P. Vogt and J. Kuhn, “Analyzing free fall with a smartphone acceleration sensor,” The Physics Teacher, vol. 50, no. 3, pp. 182–183, 2012.

[9] A. Samà, C. Angulo, D. Pardo, A. Català, and J. Cabestany, “Analyzing human gait and posture by combining feature selection and kernel methods,” Neurocomputing, vol. 74, no. 16, pp. 2665–2674, 2011.

[10] G. Hache, E. Lemaire, and N. Baddour, “Mobility change-of-state detection using a smartphone-based approach,” in Medical Measurements and Applications Proceedings (MeMeA), 2010 IEEE International Workshop on, pp. 43–46, IEEE, 2010.

[11] M. O. Derawi, “Accelerometer-based gait analysis, a survey,” Nor Informasjonssikkerhetskonferanse NISK, 2010.

[12] C. Schmid, “Ml connect.” http://mlconnect.chschmid.com/index.php/Main Page, 2012.

[13] H. Demuth, M. Beale, and M.Works, “MATLAB: Neural Network Toolbox: User’s Guide,” Math Works, 1992.

[14] J. C. Moctezuma, “Neural network toolbox de matlab,” Ciencias Computacionales, Septiembre del 2006.