A prerequisite to efficient behavior by a multi-robot team is the ability to accurately perceive the environment. In this paper, we present an approach to deal with sensing uncertainty at the coordination level. Specifically, robots attach information regarding features that caused the initiation of a course of action, to any coordination message for that activity. Further information regarding such features, acquired by the team, are then combined and the expected utility of the started action is re-evaluated accordingly. Experiments show that the approach allows to coordinate a large group of robots, addressing sensing uncertainty in a tractable way.

Dealing with Perception Errors in Multi-Robot System Coordination / A., Farinelli; P., Scerri; A., Ingenito; Nardi, Daniele. - In: IJCAI. - ISSN 1045-0823. - (2007), pp. 2091-2096. (Intervento presentato al convegno 20th International Joint Conference on Artificial Intelligence tenutosi a Hyderabad; India nel JAN 06-12, 2007).

Dealing with Perception Errors in Multi-Robot System Coordination

NARDI, Daniele
2007

Abstract

A prerequisite to efficient behavior by a multi-robot team is the ability to accurately perceive the environment. In this paper, we present an approach to deal with sensing uncertainty at the coordination level. Specifically, robots attach information regarding features that caused the initiation of a course of action, to any coordination message for that activity. Further information regarding such features, acquired by the team, are then combined and the expected utility of the started action is re-evaluated accordingly. Experiments show that the approach allows to coordinate a large group of robots, addressing sensing uncertainty in a tractable way.
2007
20th International Joint Conference on Artificial Intelligence
Coordination levels; Course of action; Expected utility
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Dealing with Perception Errors in Multi-Robot System Coordination / A., Farinelli; P., Scerri; A., Ingenito; Nardi, Daniele. - In: IJCAI. - ISSN 1045-0823. - (2007), pp. 2091-2096. (Intervento presentato al convegno 20th International Joint Conference on Artificial Intelligence tenutosi a Hyderabad; India nel JAN 06-12, 2007).
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