In this paper, we address coordination within a team of cooperative autonomous robots that need to accomplish a common goal. Our survey of the vast literature on the subject highlights two directions to further improve the performance of a multi-robot team. In particular, in a dynamic environment, coordination needs to be adapted to the different situations at hand (for example, when there is a dramatic loss of performance due to unreliable communication network). To this end, we contribute a novel approach for coordinating robots. Such an approach allows a robotic team to exploit environmental knowledge to adapt to various circumstances encountered, enhancing its overall performance. This result is achieved by dynamically adapting the underlying task assignment and distributed world representation, based on the current state of the environment. We demonstrate the effectiveness of our coordination system by applying it to the problem of locating a moving, non-adversarial target. In particular, we report on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment.

Multi-robot search for a moving target: Integrating world modeling, task assignment and context / Riccio, Francesco; Borzi, Emanuele; Gemignani, Guglielmo; Nardi, Daniele. - (2016), pp. 1879-1886. (Intervento presentato al convegno 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 tenutosi a Daejeon; South Korea nel 2016) [10.1109/IROS.2016.7759298].

Multi-robot search for a moving target: Integrating world modeling, task assignment and context

RICCIO, FRANCESCO
;
BORZI, EMANUELE;GEMIGNANI, GUGLIELMO;NARDI, Daniele
2016

Abstract

In this paper, we address coordination within a team of cooperative autonomous robots that need to accomplish a common goal. Our survey of the vast literature on the subject highlights two directions to further improve the performance of a multi-robot team. In particular, in a dynamic environment, coordination needs to be adapted to the different situations at hand (for example, when there is a dramatic loss of performance due to unreliable communication network). To this end, we contribute a novel approach for coordinating robots. Such an approach allows a robotic team to exploit environmental knowledge to adapt to various circumstances encountered, enhancing its overall performance. This result is achieved by dynamically adapting the underlying task assignment and distributed world representation, based on the current state of the environment. We demonstrate the effectiveness of our coordination system by applying it to the problem of locating a moving, non-adversarial target. In particular, we report on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment.
2016
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Control and Systems Engineering; Software; 1707; Computer Science Applications1707 Computer Vision and Pattern Recognition
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Multi-robot search for a moving target: Integrating world modeling, task assignment and context / Riccio, Francesco; Borzi, Emanuele; Gemignani, Guglielmo; Nardi, Daniele. - (2016), pp. 1879-1886. (Intervento presentato al convegno 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 tenutosi a Daejeon; South Korea nel 2016) [10.1109/IROS.2016.7759298].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/928303
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