MULTI-ROBOT DECENTRALIZED EXPLORATION USING A TRADE-BASED APPROACH

Zhi Yan (1) , Nicolas Jouandeau (1) , Arab Ali Cherif

1 LIASD - Laboratoire d'Informatique Avancée de Saint-Denis

This paper addresses the problem of exploring an unknown environment by a coordinated team of robots. An important question is, which robot should explore which region? In this paper, we present a novel decentralized task allocation approach based on trading rules for multi-robot exploration. In the decentralized system, robots can make their own decisions according to the local information with limited communication. In contrast to previous approaches, our trade-based approach is designed to simulate the relationship between buyers and sellers in a business system, to achieve dynamic task allocation by using a mechanism of unsolicited bid. Our approach has been implemented and evaluated in simulation. The experimental results demonstrate a good performance of the proposed trade-based approach compared to previous approaches.

Mots clés: Multi-robot systems; Coordinated exploration; Decentralized decision making

Domaines: Intelligence artificielle [cs.AI]

Zhi Yan, Nicolas Jouandeau, Arab Ali Cherif. MULTI-ROBOT DECENTRALIZED EXPLORATION USING A TRADE-BASED APPROACH. 8th International Conference on Informatics in Control, Automation and Robotics, Jul 2011, Noordwijkerhout, Netherlands. ⟨10.5220/0003405800990105⟩. ⟨hal-02311608⟩