Fusion of dead-reckoned positions with a workspace model for a mobile robot by Bayesian inference

Estimation of the position based on a conventional dead-reckoning for a mobile robot intrinsically contains cumulative errors. In relation to this, large nonzero probability of its error distribution is occasionally found even outside the workspace, because the dead-reckoning takes no account of the unreachability outside the workspace. This paper presents a new fusion algorithm for dead-reckoning, in which both the dead-reckoned position and the knowledge of the closed workspace are fused by means of Bayesian inference. This algorithm produces zero probability outside the workspace theoretically. Through a computer simulation, the effectiveness of the proposed algorithm is confirmed