Distributed Multi-agent Bidding-Based Approach for the Collaborative Mapping of Unknown Indoor Environments by a Homogeneous Mobile Robot Team

This paper deals with the problem of the collaborative mapping of unknown indoor environments by a homogeneous mobile robot team. For this aim, a distributed multi-agent coordination approach is proposed for the mapping process to offer a global view of the entire environment. First, the scheme starts by assigning the most suitable robots to the different zones of the environment to be mapped based on a bidding strategy. Then, while a Robot agent of the group explores its local surroundings and collects information about its neighborhood, it sends mapping data to the Human/Machine Interface agent to integrate them into a single global map. Furthermore, a geometric map representation and an algorithm based on obstacles and environment limits detection are used to provide an explicitly geometric representation of the workspace. For validation purposes, Player/Stage simulator is used to show the effectiveness of the proposed distributed approach and algorithms without needing a real multi-robot system and environment. Finally, various scenarios have been carried out and results are compared in terms of (i) required mapping time, (ii) accuracy of the global generated map, and (iii) number of exchanged messages between the agents.