In mobile robotic systems are designed for patrolling and protecting large areas, in difficult conditions, when environmental constraints severely limit the space of acceptable motions preferences, a state space sampling strategy is more effective, than sampling in the space of controls. Although this has been evident for some time, the practical question is how to achieve it while also satisfying the severe constraints of vehicle dynamic feasibility. The paper presents a new the network operator method for state space sampling utilizing a model-based trajectory generation approach. © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 13th International Symposium “Intelligent Systems” (INTELS'18).