A Hybrid Systems-based Hierarchical Control Architecture for Heterogeneous Field Robot Teams
This work addresses the need for more automated and scalable control in field robot systems, though it appears incremental as it combines existing supervisory and traditional control methods.
The study tackled the problem of managing cooperation in heterogeneous field robot teams by proposing a hybrid systems-based hierarchical control architecture, which was validated through simulation to satisfy given specifications and show systematic results.
Field robot systems have recently been applied to a wide range of research fields. Making such systems more automated, advanced, and activated requires cooperation among heterogeneous robots. Classic control theory is inefficient in managing large-scale complex dynamic systems. Therefore, the supervisory control theory based on discrete event system needs to be introduced to overcome this limitation. In this study, we propose a hybrid systems-based hierarchical control architecture through a supervisory control-based high-level controller and a traditional control-based low-level controller. The hybrid systems and its dynamics are modeled through a formal method called hybrid automata, and the behavior specifications expressing the control objectives for cooperation are designed. Additionally, a modular supervisor that is more scalable and maintainable than a centralized supervisory controller was synthesized. The proposed hybrid systems and hierarchical control architecture were implemented, validated, and then evaluated for performance through the physics-based simulator. Experimental results confirmed that the heterogeneous field robot team satisfied the given specifications and presented systematic results, validating the efficiency of the proposed control architecture.