Localization System for a Mobile Robot Using Computer Vision Techniques

Authors

  • Rony Cruz Ramírez Instituto Superior Politécnico José Antonio Echeverría
  • Maikel O. Torres Piñeiro Instituto Superior Politécnico José Antonio Echeverría
  • Valery Moreno Vega Instituto Superior Politécnico José Antonio Echeverría

Keywords:

Mobile Robotic, Computer Vision, LEGO NXT

Abstract

Mobile Robotics is a subject with multiple fields of action hence studies in this area are of vital importance. This paper describes the development of localization system for a mobile robot using Computer Vision. A webcam is placed at a height where the navigation environment can be seen. A LEGO NXT kit is used to build a wheeled mobile robot of differential drive configuration. The software is programmed in C++ using the functions library Open CV 2.0. this software then soft handles the webcam, does the processing of captured images, the calculation of the location, controls and communicates via Bluetooth. Also it implements a kinematic position control and performs several experiments to verify the reliability of the localization system. The results of one such experiment are described here.

Author Biographies

Rony Cruz Ramírez, Instituto Superior Politécnico José Antonio Echeverría

Ingeniero en Automática.Especialista B en automatización del Taller ICA de la Empresa Comercializadora de Combustibles de Matanzas-Cupet.

Maikel O. Torres Piñeiro, Instituto Superior Politécnico José Antonio Echeverría

Departamento de Automática y Computación.Facultad de Ingeniería Eléctrica. ISPJAE

Valery Moreno Vega, Instituto Superior Politécnico José Antonio Echeverría

Departamento de Automática y Computación.Facultad de Ingeniería Eléctrica. ISPJAE

Published

2012-01-21

How to Cite

Cruz Ramírez, R., Torres Piñeiro, M. O., & Moreno Vega, V. (2012). Localization System for a Mobile Robot Using Computer Vision Techniques. Revista Cubana De Ingeniería, 3(1), 29–36. Retrieved from https://rci.cujae.edu.cu/index.php/rci/article/view/61

Issue

Section

Original Articles