Research on multi-robot scheduling algorithms based on machine vision
Abstract In the multi-robot system, how to achieve effective and reasonable task coordination between multi-robots is an important problem;, multi-robot task scheduling is the term used for the coordination of the key technologies. Therefore, in this paper we combined the pilot scheduling method wit...
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Online Access: | http://link.springer.com/article/10.1186/s13640-018-0355-x |
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doaj-83dab0422f4f4e4681e1a44e7a4ec2182020-11-25T01:52:35ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812018-12-012018111110.1186/s13640-018-0355-xResearch on multi-robot scheduling algorithms based on machine visionJing Li0Fan Yang1School of Electronic and Information Engineering, Hebei University of TechnologySchool of Electronic and Information Engineering, Hebei University of TechnologyAbstract In the multi-robot system, how to achieve effective and reasonable task coordination between multi-robots is an important problem;, multi-robot task scheduling is the term used for the coordination of the key technologies. Therefore, in this paper we combined the pilot scheduling method with the following method and the behavior method of the robot based on task scheduling, and we then studied how to improve the traditional robot scheduling effect, which is a deep-learning algorithm that is applied to multi-robot scheduling to formulate an action selection strategy. We thus proved the effectiveness of this idea experimentally. Based on the above research foundation, this paper continues to build a simple simulation experiment platform, which simply sets up three obstacles and completes the task of robot scheduling on the platform.http://link.springer.com/article/10.1186/s13640-018-0355-xDeep learningMulti-robotSchedulingConvolutional neural network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jing Li Fan Yang |
spellingShingle |
Jing Li Fan Yang Research on multi-robot scheduling algorithms based on machine vision EURASIP Journal on Image and Video Processing Deep learning Multi-robot Scheduling Convolutional neural network |
author_facet |
Jing Li Fan Yang |
author_sort |
Jing Li |
title |
Research on multi-robot scheduling algorithms based on machine vision |
title_short |
Research on multi-robot scheduling algorithms based on machine vision |
title_full |
Research on multi-robot scheduling algorithms based on machine vision |
title_fullStr |
Research on multi-robot scheduling algorithms based on machine vision |
title_full_unstemmed |
Research on multi-robot scheduling algorithms based on machine vision |
title_sort |
research on multi-robot scheduling algorithms based on machine vision |
publisher |
SpringerOpen |
series |
EURASIP Journal on Image and Video Processing |
issn |
1687-5281 |
publishDate |
2018-12-01 |
description |
Abstract In the multi-robot system, how to achieve effective and reasonable task coordination between multi-robots is an important problem;, multi-robot task scheduling is the term used for the coordination of the key technologies. Therefore, in this paper we combined the pilot scheduling method with the following method and the behavior method of the robot based on task scheduling, and we then studied how to improve the traditional robot scheduling effect, which is a deep-learning algorithm that is applied to multi-robot scheduling to formulate an action selection strategy. We thus proved the effectiveness of this idea experimentally. Based on the above research foundation, this paper continues to build a simple simulation experiment platform, which simply sets up three obstacles and completes the task of robot scheduling on the platform. |
topic |
Deep learning Multi-robot Scheduling Convolutional neural network |
url |
http://link.springer.com/article/10.1186/s13640-018-0355-x |
work_keys_str_mv |
AT jingli researchonmultirobotschedulingalgorithmsbasedonmachinevision AT fanyang researchonmultirobotschedulingalgorithmsbasedonmachinevision |
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1724994317889568768 |