Improving vision-based self-localization

Abstract

After removing the walls around the field, vision-based localization has become an even more interesting approach for robotic soccer. The paper discusses how removal of the wall affects the localization task in ROBOCUP, both for vision-based and non-visual approaches, and argues that vision-based Monte Carlo localization based on landmark features seems to cope well with the changed field setup. An innovative approach for landmark feature detection for vision-based Monte Carlo Localization is presented. Experimental results indicate that the approach is robust and reliable. © Springer-Verlag Berlin Heidelberg 2003.