Study of classification of failure states for Small Unmanned Ground Vehicle by response surface methodology

SUGV(Small Unmanned Ground Vehicle) used for human rescue and military operation is need to overcome the environment that tough terrains such as a hole or high obstacles. As far as the survival of the vehicle and the preserving ability of the information in the vehicle are concerned, it is essential to have an approach for recognizing unattainable driving states. However, despite the fact that the study of obstacle avoidance and stabilization of SUGV is focused on, it is hardly found out ways of classifying unattainable driving states with the sensors mounted on the SUGV unit. In order to overcome the problem, this paper proposes a practical way for classifying SUGV Failure State(SFS) with the meaningful parameters by statistical method, response surface methodology(RSM).