Improved Lateral Stability for Unmanned Ground Vehicle Convoys

Unmanned automated convoys provide an efficient means for transporting the cargo of many vehicles across the same terrain to reach a desired location. As more vehicles are added, the efficiency of the convoy can increase; however, if each successive vehicle uses the previous vehicle for path following, the convoy accuracy will gradually degrade. In order to improve the path following of successive vehicles, the phase I of this project showed that use of disturbance and off-path error information can improve the accuracy of successive vehicles by passing this information to the following vehicle. The phase II of this project will continue to build on this idea, utilizing more general disturbance estimations. Additionally, improving the dynamic models of the vehicles and using preview information of the path with AMAS sensors will improve prediction steps of the Kalman filter and path control in general. This project will utilize ASIs large assortment of equipment and vehicles with expertise from Auburn University and their AMAS sensor suite to ensure success of this project. Successful completion of this project will provide benefits to both manned and unmanned ground vehicles. Commercialization efforts will be an important part of this project.