Special issue "Sensor Fusion". A Position Estimation which Takes Account of a Closed Space Model for a Mobile Robot-A Bayesian Fusion Method Using Internal Sensory Data and Knowledge about Work Space.

Abstract

A conventional dead-reckoning that estimates a mobile robot position induces cumulative errors intrinsically. Nonzero probability of its error distribution is occasionally found even outside the work space, because the dead-reckoningtakes no account of the closed extent of the work space. This paper presents a new estimation algorithm for deadreckoning that fuses the knowledge of the closed work space with position estimates by means of Bayesian inference.This new algorithm produces zero probability outside the work space theoretically. Through a computer simulation, the effectiveness of the proposed algorithm is confirmed.