Navigation with uncertain position estimation in the RAM-1 mobile robot

Abstract

This paper studies the uncertainty in mobile robot navigation. The paper presents a model to propagate the uncertanty in position and orientation when tracking a given path. The model assumes normal distribution with zero means and a covariance matrix which can be computed recursively using the kinematics. The paper also presents the application to the mobile robot RAM-1 designed and built for navigation in outdoor and indoor industrial environments. The proposed method can be used in the navigation system to know the position uncertainty before the vehicles executes a given path. Furthermore, the method is also useful to plan the execution of computationally intensive vision and other external perception functions which are required to avoid the uncertainty growing during navigation.