Robotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace.This work was financed by national funds from the FCT (Foundation for Science and
Technology), I.P., through IDMEC under LAETA, project UIDB\50022\2020. The work of Rodrigo
Bernardo was supported by the PhD Scholarship BD\6841\2020 from the FCT. This work indirectly
received funding from the European Union’s Horizon 2020 programme under StandICT.eu 2026
(Grant Agreement No. 101091933).info:eu-repo/semantics/publishedVersio
