The effect of intermittent measurement in Simultaneous Localization and Mapping

Abstract

Intermittent measurement is defined as a situation where a mobile robot experiences loss of measurement data during observation due to sensor failure or imperfection of the system. The impact of intermittent measurement on the Simultaneous Localization and Mapping (SLAM) of a mobile robot is the subject of this paper. The analysis is important since SLAM requires recursive measurement data update throughout the process. In this paper, the effect of intermittent measurement on the state error covariance matrix was analyzed on two basic conditions, which are when the mobile robot is stationary and when it is in motion. We have observed the impact on the determinant of covariance matrix. It is proven by our analysis that intermittent measurement could cause inaccurate estimation of robot's position and might increase the state error covariance matrix.