Dina A. Amer, G. Attiya, Ibrahim Zeidan, Aida A. Nasr
{"title":"Employment of Task Scheduling based on Water Wave Optimization in Multi Robot System","authors":"Dina A. Amer, G. Attiya, Ibrahim Zeidan, Aida A. Nasr","doi":"10.1109/ICEEM52022.2021.9480617","DOIUrl":null,"url":null,"abstract":"The task allocation problem in a multi-robot system (MRS) may be characterized as the problem of assigning a set of tasks to a group of robots in order to improve some performance parameters. However, when many requests are received simultaneously by a robot, the current scheduling approaches may make unreasonable decisions, delaying the execution of some requests and so affecting the system performance. This paper addresses this issue and proposes a new scheduling mechanism for task allocation in MRS. The presented approach implements a universal allocation depend on Water Wave Optimization (WWO) algorithm with the Genetic Algorithm (WWO_GA). The result of this approach is compared with the conventional Water Wave Optimization (WWO) and the Particle Swarm Optimization (PSO) algorithms. Simulation results prove that the introduced approach enhances the performance of the multi-robot system in terms of total traveled distance and computation time.","PeriodicalId":352371,"journal":{"name":"2021 International Conference on Electronic Engineering (ICEEM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Electronic Engineering (ICEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEM52022.2021.9480617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The task allocation problem in a multi-robot system (MRS) may be characterized as the problem of assigning a set of tasks to a group of robots in order to improve some performance parameters. However, when many requests are received simultaneously by a robot, the current scheduling approaches may make unreasonable decisions, delaying the execution of some requests and so affecting the system performance. This paper addresses this issue and proposes a new scheduling mechanism for task allocation in MRS. The presented approach implements a universal allocation depend on Water Wave Optimization (WWO) algorithm with the Genetic Algorithm (WWO_GA). The result of this approach is compared with the conventional Water Wave Optimization (WWO) and the Particle Swarm Optimization (PSO) algorithms. Simulation results prove that the introduced approach enhances the performance of the multi-robot system in terms of total traveled distance and computation time.