移動ロボットにおける空間有限性を考慮した位置推定

―内界センサ情報と作業領域に関する知識のベイズ的融合法―

抄録

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.