Open AccessUsing the Hopfield Neural Network to Select a Behaviour Strategy for the Group of Mobile Robots
Author(s) -
O.V. Darintsev,
A.B. Migranov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2096/1/012086
Subject(s) - workspace , computer science , artificial neural network , robot , mobile robot , artificial intelligence , problem statement , hopfield network , graph , metaheuristic , heuristic , task (project management) , group (periodic table) , mathematical optimization , theoretical computer science , mathematics , engineering , chemistry , systems engineering , organic chemistry , management science
The use of the Hopfield neural network for the task distribution problem solving in teams of mobile robots performing monosyllabic operations in a single workspace is considered. The study is a continuation of earlier works in which the same problem was solved by the authors using other heuristic algorithms – swarm and genetic. This article presents the problem statement and the model of the working space, distinguishes the goals of robotic operation. The quality indicator is the total distance traveled by each of the robots in the group. To enable the original problem to be solved using the Hopfield neural network, a graph representation of the Hopfield is made by switching from the VRP to the TSP problem. The results of computational experiments confirming the effectiveness of the chosen approach for choosing a strategy of behavior of a group of mobile robots are shown.