UM  > 科技學院  > 機電工程系
Robust GA Based Global Path Planning for IoP Oriented Mobil Robot
Ruidong Xi1; Zhixin Yang1; Lulu Tang1; Zhigang Wang2
2018
Conference Name2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Source Publication2018 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION
Conference Date8-12 Oct. 2018
Conference PlaceGuangzhou, China
Abstract

In this paper, a novel genetic algorithm based global path planning approach is proposed for effective and robust control of an IoP-oriented mobile robot. This method is designed in an indoor work environment, different from the traditional procedure of planning algorithm, a searching area is determined at first, within which the subsequent planning method is conducted. The improved genetic algorithm method exploits a new encoding scheme to increase the chromosomes' flexibility and adopts a new crossover operator for effectiveness. The simulation results in MATLAB successfully demonstrate that the proposed method performs very well in various environments.

DOIhttps://www.doi.org/10.1109/SmartWorld.2018.00328
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000458742900292
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Affiliation1.Univ Macau, Fac Sci & Technol, Macau, Peoples R China
2.Jiangxi Univ Sci & Technol, Sch Energy & Machinery Engn, Nanchang, Jiangxi, Peoples R China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ruidong Xi,Zhixin Yang,Lulu Tang,et al. Robust GA Based Global Path Planning for IoP Oriented Mobil Robot[C],2018.
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