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An Auto-Adaptive Multi-Objective Strategy for Multi-Robot Exploration of Constrained-Communication Environments

Facundo Benavides, Caroline Ponzoni Carvalho Chanel, Pablo Monzón, Eduardo Grampín

Year
2019
Citations
17
Access
Open access

Abstract

The exploration problem is a fundamental subject in autonomous mobile robotics that deals with achieving the complete coverage of a previously unknown environment. There are several scenarios where completing exploration of a zone is a main part of the mission. Due to the efficiency and robustness brought by multi-robot systems, exploration is usually done cooperatively. Wireless communication plays an important role in collaborative multi-robot strategies. Unfortunately, the assumption of stable communication and end-to-end connectivity may be easily compromised in real scenarios. In this paper, a novel auto-adaptive multi-objective strategy is followed to support the selection of tasks regarding both exploration performance and connectivity level. Compared with others, the proposed approach shows effectiveness and flexibility to tackle the multi-robot exploration problem, being capable of decreasing the last of disconnection periods without noticeable degradation of the completion exploration time.

Keywords

Computer scienceRobotFlexibility (engineering)Artificial intelligenceRobustness (evolution)Mobile robotRoboticsDistributed computingControl engineeringHuman–computer interaction

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