Methods for Minimizing Navigation Errors Induced by Ground Vehicle Dynamics

Abstract

A navigation system was designed using an extended Kalman filter for an autonomous ground vehicle competing in the 2005 DARPA Grand Challenge. An overview of this system is provided, and errors in the navigation solution are explained. These errors are attributed to vehicle dynamics unaccounted for in the navigation model.

Investigation of these errors begins with the development of a nonlinear simulation to provide vehicle state information in a controlled environment. These vehicle states are used in various navigation models to show difference in navigation accuracy when lateral vehicle dynamics are taken into account. Accuracy with and without GPS measurements is examined. The study then utilizes experimental data to provide similar results. Also, sources of error stemming from typical velocity sensors are explained.

Finally, a method is proposed to utilize a laser scanner to provide measurements for use in the navigation models incorporating lateral vehicle motion. This method could also be used to provide a vehicle controller lateral error from a defined corridor. The method is explained, and experimental results from a simple test bed are shown.