scholarly journals Using the Hopfield Neural Network to Select a Behaviour Strategy for the Group of Mobile Robots

2021 ◽  
Vol 2096 (1) ◽  
pp. 012086
Author(s):  
O V Darintsev ◽  
A B Migranov

Abstract 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.

Author(s):  
WEN-FENG KUO ◽  
CHI-YUAN LIN ◽  
YUNG-NIEN SUN

A robust image segmentation method that combines the watershed segmentation and penalized fuzzy Hopfield neural network (PFHNN) algorithms to minimize undesirable over-segmentation is described in this paper. This method incorporates spatial graph representation derived from the watershed segmented regions and cluster analysis information obtained from the PFHNN algorithm to achieve efficient image segmentation. The proposed scheme employs the Markov random field (MRF) model on the region adjacency graph (RAG) to improve the quality of watershed segmentation. Here, the fusion criterion is according to the correlation coefficient, which uses inter-region similarities to determine the merging of regions. Analysis of the performance of the proposed technique is presented through quantitative and qualitative validation experiments on benchmark images, and significant and promising segmentation results are presented using brain phantom simulated data.


2009 ◽  
Vol 29 (4) ◽  
pp. 1028-1031
Author(s):  
Wei-xin GAO ◽  
Xiang-yang MU ◽  
Nan TANG ◽  
Hong-liang YAN

2006 ◽  
Vol 13B (3) ◽  
pp. 323-328
Author(s):  
Yukhuu Ankhbayar ◽  
Suk-Hyung Hwang ◽  
Young-Sup Hwang

2010 ◽  
Vol 7 ◽  
pp. 109-117
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov ◽  
B.S. Yudintsev

The article deals with the development of a high-speed sensor system for a mobile robot, used in conjunction with an intelligent method of planning trajectories in conditions of high dynamism of the working space.


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