First published 2 September 2013
Evaluation of an Experimental Framework for Exploiting Vision in Swarm Robotics
Sjriek Alers, Bijan Ranjbar-Sahraei, Stefan May, Karl Tuyls, Gerhard Weiss
Visual feature detection with limited resources of simple robots is an essential requirement for swarm robotic systems. Robots need to localize their position, to determine their orientation, and need to be able to acquire extra information from their surrounding environment using their sensors, while their computational and storage capabilities might be very limited. This paper evaluates the performance of an experimental framework, in which environmental elements such as landmarks and QR-codes are considered as key visual features. The performance is evaluated for environmental light disturbances and distance variations and feature detection speed is thoroughly examined. The applicability of the approach is shown in a real robot scenario by using e-puck robots. Finally, the results of applying the approach to a completely different setting, i.e., simulation of pheromones using glowing trail detection, are presented. These results indicate the broad applicability range of the developed feature detection techniques.