Title: Fuzzy predictor for parallel dynamic task allocation in multi-robot systems

Authors: Hamza Teggar; Mohamed Senouci; Fatima Debbat

Addresses: Department of Computer Sciences, Faculty of Exact Sciences, University Ahmed Ben Bella Oran 1, Oran, Algeria ' Department of Computer Sciences, University Ahmed Ben Bella Oran 1, National Polytechnic School Maurice Audin of Oran, ENP D'Oran Ex ENSET, Rue D, Es Senia, 31000, Algeria ' Department of Computer Sciences, Faculty of Exact Sciences, University Mustapha Stanbouli, Mascara, Algeria

Abstract: This paper presents a model to decompose complex tasks in the form of elemental tasks executed in parallel by multi robots. In this model, a criterion of accuracy in the parallel dynamic tasks allocation process (APDTA) is defined. Through this APDTA, a predictor based on fuzzy logic called FP-TE is developed to evaluate the importance of elemental tasks in the system. The inputs of this predictor are described as observations acquired from sensor data. The FP-TE output will be used to allow each robot to individually decide what task should be executed. Simulation results on goods transportation by mobile robots are presented to demonstrate the effectiveness of this fuzzy predictor.

Keywords: dynamic tasks allocation; multi-robot systems; fuzzy predictor; accuracy in tasks allocation; distributed MRS.

DOI: 10.1504/IJCAET.2021.115944

International Journal of Computer Aided Engineering and Technology, 2021 Vol.15 No.1, pp.12 - 31

Received: 11 Apr 2018
Accepted: 29 Oct 2018

Published online: 12 May 2021 *

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