Skip to Main content Skip to Navigation
Conference papers

Multi-agents based system to coordinate mobile teamworking robots

Abstract : This paper aims at presenting the Multi-Agents System to Control and Coordinate teAmworking Robots (MAS2CAR), a new architecture to control a group of coordinated autonomous robots in un-structured environments. MAS2CAR covers two main layers: (i) the Control Layer and we focus on (ii) the Coordination Layer. The control module is responsible for a part of the decision making process taking into account robot's structural constraints. Despite this autonomy possibility, the Coordination Layer manages the robots in order to bring cooperative behavior and to allow teamwork. In this paper we present a scenario validating our approach based upon the multi-agent systems (MAS). Thanks to its reliability we have chosen the Moise Inst organizational model and we will present how it can be used for this use-case. Moreover, regarding to the implementation part, we have retained Utopia, a framework which automatically build a MAS thanks to a Moise Inst specification. We will present key problematics of the Cooperation Layer implementation solved thanks to Utopia and exhibit robotic cooperative behavior related to our scenario through simulation results.
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01714861
Contributor : Lounis Adouane <>
Submitted on : Friday, February 23, 2018 - 1:21:24 AM
Last modification on : Wednesday, September 9, 2020 - 10:50:04 AM
Long-term archiving on: : Thursday, May 24, 2018 - 12:36:51 PM

File

2010_Mouad_CRW.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01714861, version 1

Citation

Mehdi Mouad, Lounis Adouane, Pierre Schmitt, Djamel Khadraoui, Benjamin Gâteau, et al.. Multi-agents based system to coordinate mobile teamworking robots. 4th Companion Robotics Workshop, Sep 2010, Brussels, Belgium. ⟨hal-01714861⟩

Share

Metrics

Record views

377

Files downloads

144