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Applied Sciences
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Multi-Robot Systems: Theory, Modeling and Applications
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Multi-Robot Systems: Theory, Modeling and Applications

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: closed (15 September 2022) | Viewed by 2100

Special Issue Editor

Prof. Dr. Nuno Miguel Fonseca Ferreira

E-Mail Website
Guest Editor
Department of Electrical Engineering, Polytechnic of Coimbra, P-3004 516 Coimbra, Portugal
Interests: industrial robotics; automation; cooperative robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue on Multi-Robot Systems provides a broad sampling of the research that is currently ongoing in the field. To help categorize this research, we have identified the following topics within multi-robot systems—biological inspirations; communication; architectures; localization; mapping; exploration; object transport and manipulation; motion coordination; reconfigurable robot transport and manipulation; motion coordination; and reconfigurable robots. Several new robotics application areas, such as underwater and space exploration, hazardous environments, service robotics in both public and private domains, the entertainment field, and so forth, can benefit from the use of multi-robot systems. This Special Issue will be of interest mainly to scientists, researchers, and students working in multi-robot systems, but it could also be interesting to other readers interested in the more general areas of robotics and control.

Dr. Nuno Miguel Fonseca Ferreira
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

21 pages, 5048 KiB  
Article
Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line
by Ya Hu, Xing Wu, Jingjing Zhai, Peihuang Lou, Xiaoming Qian and Haining Xiao
Appl. Sci. 2022, 12(21), 10956; https://doi.org/10.3390/app122110956 - 28 Oct 2022
Cited by 1 | Viewed by 1652
Abstract
An AGV system can be used to transport different-size materials in an assembly line. The hybrid task allocation problem is involved in the assembly line, where both single-AGV tasks and multi-AGV tasks exist. However, there is little research on this problem. The goal [...] Read more.
An AGV system can be used to transport different-size materials in an assembly line. The hybrid task allocation problem is involved in the assembly line, where both single-AGV tasks and multi-AGV tasks exist. However, there is little research on this problem. The goal of solving this problem is to obtain a task allocation scheme with minimum idle time and maximum system throughput. Since all necessary materials must be delivered to the assembly station before the operation can start, the delivery tasks are not independent of each other in a task group serving the operation. To solve the problem above, a hybrid task allocation method based on a task binding strategy and an improved particle swarm optimization (IPSO) is proposed. Firstly, a mathematical model considering the punctuality of material delivery and the cooperative relationship between tasks is established. Secondly, a task binding strategy and four heuristic rules are devised to improve the quality of randomly- and heuristic-generated individuals in the initial population for model optimization. Thirdly, an IPSO is developed to help the optimization algorithm jump out of local optimums. Finally, a simulation is performed to verify the effectiveness of the proposed methods. The simulation results show that a better scheme can be obtained by our hybrid task allocation method, compared to conventional Genetic Algorithms and PSO algorithms. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Theory, Modeling and Applications)
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