Unmanned Aerial Vehicles (UAVs) and in particular quad-rotors are gaining an increasing interest owing to their flexibility and versatility. Today the challenge is to integrate these versatile platforms in a wide fleet in order to perform cooperative tasks as surveillance, search & rescue, inspection. The coalition formation problem is a pre-condition for cooperative missions. This problem can be solved with different methodologies from biologically-inspired algorithms to parasocial consensus sampling ones. In this paper a new framework for simulation of unmanned vehicles in cooperative scenarios is first presented. Then a novel method that exploits the benefits of Model Predictive Control (MPC) for a coalition formation problem (leader-follower) is introduced. The obtained results evidence the good performance of MPC to solve the problem of coalition formation for unmanned aerial vehicles finding the optimal solution taking into account different kind of constraints. The developed framework allows also to easily change from simulated agent to real one.
A simulation framework for coalition formation of Unmanned Aerial Vehicles / Benini, Alessandro; Mancini, Adriano; Frontoni, Emanuele; Zingaretti, Primo; Longhi, Sauro. - (2011), pp. 406-411. (Intervento presentato al convegno 2011 19th Mediterranean Conference on Control and Automation (MED) tenutosi a Corfu, Greece nel 20-23 June 2011) [10.1109/MED.2011.5983163].
A simulation framework for coalition formation of Unmanned Aerial Vehicles
BENINI, ALESSANDRO;MANCINI, ADRIANO;FRONTONI, EMANUELE;ZINGARETTI, PRIMO;LONGHI, SAURO
2011-01-01
Abstract
Unmanned Aerial Vehicles (UAVs) and in particular quad-rotors are gaining an increasing interest owing to their flexibility and versatility. Today the challenge is to integrate these versatile platforms in a wide fleet in order to perform cooperative tasks as surveillance, search & rescue, inspection. The coalition formation problem is a pre-condition for cooperative missions. This problem can be solved with different methodologies from biologically-inspired algorithms to parasocial consensus sampling ones. In this paper a new framework for simulation of unmanned vehicles in cooperative scenarios is first presented. Then a novel method that exploits the benefits of Model Predictive Control (MPC) for a coalition formation problem (leader-follower) is introduced. The obtained results evidence the good performance of MPC to solve the problem of coalition formation for unmanned aerial vehicles finding the optimal solution taking into account different kind of constraints. The developed framework allows also to easily change from simulated agent to real one.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.