An Educational Software to Develop Robot Mapping and Localization Practices Using Visual Information

Abstract In this work, we present a software tool we have developed to be used in a computer vision and mobile robotics subject whose main objective consists in designing algorithms to control an autonomous robot. In applications that require the robot to move through an unknown environment, it is very important to build a model or map of this environment and to estimate the position of the robot in this map with enough accuracy. Map building and localization are two topics in constant innovation as new methods are continuously appearing, and some of these methods may be mathematically complex. Taking this fact into account, we have designed a platform that provides students all the necessary tools to understand the algorithms and that allows students to configure them to optimize the mapping and localization processes. We have added some databases, composed of several sets of indoor images, captured in real environments under realistic lighting conditions, so students will face the problems that would outcome in a real application. In this paper we present some details of implementation of the platform and how the students could use it.

[1]  Emanuele Menegatti,et al.  Image-based memory for robot navigation using properties of omnidirectional images , 2004, Robotics Auton. Syst..

[2]  Sabine Grunwald,et al.  Development of an environmental virtual field laboratory , 2005, Comput. Educ..

[3]  Ben J. A. Kröse,et al.  Household robots look and learn: environment modeling and localization from an omnidirectional vision system , 2004, IEEE Robotics & Automation Magazine.

[4]  Antonio Torralba,et al.  Contextual Priming for Object Detection , 2003, International Journal of Computer Vision.

[5]  Fernando Torres Medina,et al.  Hands-on experiences of undergraduate students in Automatics and Robotics using a virtual and remote laboratory , 2011, Comput. Educ..

[6]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[7]  M. Bergerman,et al.  A robotics and computer vision virtual laboratory , 1998, AMC'98 - Coimbra. 1998 5th International Workshop on Advanced Motion Control. Proceedings (Cat. No.98TH8354).

[8]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).