A probabilistic approach to Hough localization

Abstract
Autonomous navigation for mobile robots performing complex tasks over long periods of time requires eec- tive and robust self-localization techniques. In this paper we describe a probabilistic approach to self- localization that integrates Kalman Þltering with map matching based on the Hough Transform. Several sys- tematic experiments for evaluating the approach have been performed both on a simulator and on soccer robots embedded in the RoboCup environment.

This publication has 6 references indexed in Scilit: