In this paper, we study existing flocking models and propose extensions to improve their abilities to deal with environments having obstacles impacting the communication quality. Often depicted as robust systems, there is yet a lack of understanding how flocking models compare and how they are impacted by the communication quality when they exchange control data. We extend two standard models to improve their ability to stay connected while evolving in environments with different obstacles distributions. By taking into account the radio propagation, we model the obstacles impact on communications in a simulator that we use to optimize flocking parameters. The simulation results show the efficiency of the proposed models and how they adapt to different environmental constraints.