Position estimation is one of the classic problems in mobile
robotics. The goal of this paper is to compare two probabilistic localization
methods based on local vision for a mobile robot. The experimental
set up is based on the Aibo league of the RoboCup, where the robotic
dogs major sensor is the on-board camera. Two localization algorithms,
Bayesian and Montecarlo (MCL), have been implemented and compared,
and their behaviour studied in several situations using a simulator
