Passivity-based model predictive control for mobile robot navigation planning in rough terrains

This paper presents a novel navigation and motion planning algorithm for mobile vehicles in rough terrains. The main purpose of the algorithm is to generate feasible trajectories while selecting smoother paths, in the sense of level of roughness, toward the goal position. The purpose is achieved by adapting the passivity-based model predictive control optimization setup (PB/MPC), recently proposed for flat terrains, to the case of an outdoor irregular terrain. The passivity-based concept is used to enhance MPC in order to stabilize the goal position guaranteeing the task completion. The framework which is obtained can exploit any vehicle model in order to carefully take into account the vehicle dynamics and terrain structure as well as the wheel-terrain interaction. The inherited property of the MPC optimization allows to impose any additional constraint into the PB/MPC navigation, such as those needed to prevent vehicle rollover and unnecessary sideslip. The cost function representing the level of roughness along a candidate path is used to select the appropriate terrain areas toward the goal position. The results have been verified by several simulation examples.