Fuzzy Arm Controller for Critical Slope Crossing and QuasiRotational Strategy for Intense Bump Crossing

Research shows that most of the damage to off-road vehicles is due to a lack of balance in critical situations. This paper is studying the impact of the arm on tracked vehicle trafficability on critical slopes. The position and weight of the arm have a direct effect on the position and location of the tracked vehicle s center of mass. The neural network is used to find the function between the position of the vehicle s center of mass and the maximum slope traverse ability. The neural network is trained using experimental data. In this study, while investigating the effect of arm position on vehicle trafficability, a fuzzy control system is designed to maintain a tracked vehicle balance at a critical slope. This controller prevents the tracked vehicle from tip-over on the critical slope. Based on vehicle speed control, a controlling system is also designed for crossing the bump. A quasi-rotational motion for a tracked vehicle, makes it possible to cross the bump which it cannot pass in normal condition. The small tracked vehicle is equipped for trafficability experiments. The pitch angle is compared and validated between simulations and experiments.