Characterization of the impact of visual odometry drift on the control of an autonomous vehicle

Autonomous vehicle navigation requires the desired trajectory and the current localization to be able to calculate the command that must be sent to the actuators. The localization of the vehicle (usually defined by a position vector and an orientation vector), can be provided by external systems. GPS localization is the most accurate solution but when it is no longer available or precise, an on-board localization estimation based on proprioceptive and exteroceptive sensors is needed. Visual odometry is a well-known approach to estimate the vehicle motion from a camera. Unfortunately, visual localization is subject to errors that increase over time (drift). In this paper, we provide a study of the impact of localization errors on the control of an autonomous vehicle. In order to validate visual odometry algorithms in simulation, a drift model is proposed. Real navigation experiments with errors on the localization are presented to characterize the drift model and the propagation of localization errors in the controller module and the associated command signal.