This paper describes a decentralized approach to control the execution of a set of tasks for a network of heterogeneous robotic agents, i.e., agents with different sets of sensors and actuators. The proposed approach is based on a discrete-event modeling and control framework. The novelty is the full decoupling between the tasks modeling and their deployment. This implies an higher robustness to faults in the network of agents and a more systematic way for the task modeling regardless of the actual capability of the agents. A consensus-based mechanism is exploited in the control system to achieve coherence among the agents state and synchronize the agents action.

Decentralized Discrete-Event Modeling and Control of Task Execution for Robotic Networks, / DI PAOLA, Donato; Gasparri, A.; Naso, David; Lewis, F. L.. - (2012), pp. 7346-7351. (Intervento presentato al convegno 51st IEEE Conference on Decision and Control, CDC 2012 tenutosi a Maui, Hawaii nel 10-13 December 2012) [10.1109/CDC.2012.6426687].

Decentralized Discrete-Event Modeling and Control of Task Execution for Robotic Networks,

DI PAOLA, DONATO;NASO, David;
2012-01-01

Abstract

This paper describes a decentralized approach to control the execution of a set of tasks for a network of heterogeneous robotic agents, i.e., agents with different sets of sensors and actuators. The proposed approach is based on a discrete-event modeling and control framework. The novelty is the full decoupling between the tasks modeling and their deployment. This implies an higher robustness to faults in the network of agents and a more systematic way for the task modeling regardless of the actual capability of the agents. A consensus-based mechanism is exploited in the control system to achieve coherence among the agents state and synchronize the agents action.
2012
51st IEEE Conference on Decision and Control, CDC 2012
978-1-4673-2066-5
Decentralized Discrete-Event Modeling and Control of Task Execution for Robotic Networks, / DI PAOLA, Donato; Gasparri, A.; Naso, David; Lewis, F. L.. - (2012), pp. 7346-7351. (Intervento presentato al convegno 51st IEEE Conference on Decision and Control, CDC 2012 tenutosi a Maui, Hawaii nel 10-13 December 2012) [10.1109/CDC.2012.6426687].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/16098
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