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Applied Sciences
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Multi-Robot Systems and Their Applications
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Multi-Robot Systems and Their Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (30 May 2023) | Viewed by 5286

Special Issue Editors

Dr. Alexandre Brandão

E-Mail Website
Guest Editor
Núcleo de Especialização em Robótica (NERO), Department of Electrical Engineering, Graduate Program in Computer Science, Universidade Federal de Viçosa, Viçosa 36570-900, Minas Gerais, Brazil
Interests: nonlinear control; unmanned aerial and ground vehicles; cooperative navigation
Special Issues, Collections and Topics in MDPI journals
Dr. Martin Saska

E-Mail Website
Guest Editor
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36 Prague 6, Czech Republic
Interests: motion planning; swarm robotics; modular robotics; robotic simulators
Special Issues, Collections and Topics in MDPI journals
Dr. Pedro Castillo Garcia

E-Mail Website
Guest Editor
Heudiasyc Laboratory, UMR CNRS 7253, Universite de Technologie de Compiègne, 60203 Compiegne, France
Interests: non-linear control; delays systems and predictors; observers; autonomous vehicles; data fusion; robust navigation; real-time control; robotics

Special Issue Information

Dear Colleagues,

Robotics researchers are aware that certain tasks are more efficiently performed by a group of robots acting cooperatively rather than a single robot. This is due to the inherent characteristics of the task to be performed or the associated cost if performed by a specialized robot. As an analogy with biological systems, there are several communities in nature that work cooperatively and are able to group, disperse and/or move collectively, using simple control rules. This is the case, for example, with ants, bees, birds, and fish.

To address this type of navigation problem, in the context of robotics, this Special Issue on “Multi-Robot System and Their Applications" is dedicated to publishing research papers, communications, and review articles proposing solutions for problems that are more efficiently solved by a group of robotic agents, such as collective entertainment games, cargo transportation, search and rescue missions, mapping, the surveillance of large areas, and even space exploration.

This Special Issue aims to attract the state-of-the-art in the theory of multi-robot systems and their applications. Topics of interest may include, but are not limited to, the following:

  • Swarming and modular robot systems;
  • Behavior- and consensus-based approaches;
  • Virtual structure and leader–follower strategies;
  • Flexible and fault tolerant solutions for multi-robot systems;
  • Cooperative and collaborative communication, localization, and navigation;
  • Modeling and control of multi-robot systems using artificial intelligence techniques.

Dr. Alexandre Brandão
Dr. Martin Saska
Dr. Pedro Castillo Garcia
Guest Editors

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 (3 papers)

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Research

16 pages, 8189 KiB  
Article
Robot Formation Performing a Collaborative Load Transport and Delivery Task by Using Lifting Electromagnets
by Celso Oliveira Barcelos, Leonardo Alves Fagundes-Júnior, Daniel Khéde Dourado Villa, Mário Sarcinelli-Filho, Amanda Piaia Silvatti, Daniel Ceferino Gandolfo and Alexandre Santos Brandão
Appl. Sci. 2023, 13(2), 822; https://doi.org/10.3390/app13020822 - 06 Jan 2023
Cited by 2 | Viewed by 1381
Abstract
This paper presents a practical validation of a heterogeneous formation of mobile robots in performing a load lifting, transportation, and delivery task. Assuming that an unmanned ground vehicle (UGV) is unable to perform a mission by itself due to the presence of an [...] Read more.
This paper presents a practical validation of a heterogeneous formation of mobile robots in performing a load lifting, transportation, and delivery task. Assuming that an unmanned ground vehicle (UGV) is unable to perform a mission by itself due to the presence of an obstacle in the navigation route, an unmanned aerial vehicle (UAV) is then assigned to lift the cargo over this UGV, transport the obstacle, and deliver over another UGV. The UAV uses an electromagnetic actuator supported by a cable to pick up the load, the mass of which is 32% of that of the UAV. Experimental results demonstrate that the developed system is capable of performing cargo transport missions and can be scalable for applications such as package delivery in urban or remote areas and supply delivery in conflict or disaster zones. Full article
(This article belongs to the Special Issue Multi-Robot Systems and Their Applications)
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19 pages, 32652 KiB  
Article
CONCERTS: Coverage Competency-Based Target Search for Heterogeneous Robot Teams
by Minkyu Kim, Ryan Gupta and Luis Sentis
Appl. Sci. 2022, 12(17), 8649; https://doi.org/10.3390/app12178649 - 29 Aug 2022
Cited by 3 | Viewed by 1515
Abstract
This paper proposes CONCERTS: Coverage competency-based target search, a failure-resilient path-planning algorithm for heterogeneous robot teams performing target searches for static targets in indoor and outdoor environments. This work aims to improve [...] Read more.
This paper proposes CONCERTS: Coverage competency-based target search, a failure-resilient path-planning algorithm for heterogeneous robot teams performing target searches for static targets in indoor and outdoor environments. This work aims to improve search completion time for realistic scenarios such as search and rescue or surveillance, while maintaining the computational speed required to perform online re-planning in scenarios when teammates fail. To provide high-quality candidate paths to an information-theoretic utility function, we split the sample generation process into two steps, namely Heterogeneous Clustering (H-Clustering) and multiple Traveling Salesman Problems (TSP). The H-Clustering step generates plans that maximize the coverage potential of each team member, while the TSP step creates optimal sample paths. In situations without prior target information, we compare our method against a state-of-the-art algorithm for multi-robot Coverage Path Planning and show a 9% advantage in total mission time. Additionally, we perform experiments to demonstrate that our algorithm can take advantage of prior target information when it is available. The proposed method provides resilience in the event of single or multiple teammate failure by recomputing global team plans online. Finally, we present simulations and deploy real hardware for search to show that the generated plans are sufficient for executing realistic missions. Full article
(This article belongs to the Special Issue Multi-Robot Systems and Their Applications)
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25 pages, 6507 KiB  
Article
Enhanced Hybrid Ant Colony Optimization for Machining Line Balancing Problem with Compound and Complex Constraints
by Junyi Hu, Zeqiang Zhang, Haixuan Qiu, Junbo Zhao and Xuechen Xu
Appl. Sci. 2022, 12(9), 4200; https://doi.org/10.3390/app12094200 - 21 Apr 2022
Cited by 3 | Viewed by 1437
Abstract
Targeted at the machining production line balancing problem, based on the precedence constraint relation of the present machining task, this article suggests adding practical constraints such as advanced station preparations, post-auxiliary tasks, and tool changing. The study introduced ‘tight’ and ’or’ constraints to [...] Read more.
Targeted at the machining production line balancing problem, based on the precedence constraint relation of the present machining task, this article suggests adding practical constraints such as advanced station preparations, post-auxiliary tasks, and tool changing. The study introduced ‘tight’ and ’or’ constraints to bring the problem definition closer to the actual situation. For this problem, a mixed-integer programming model was constructed in this study. The model redefines the machining and auxiliary processing tasks and adds new time constraints to the station. The model considers two optimisation objectives: the number of stations and the machining line balancing rate. In view of the complexity of the problem, heuristic task set filtering mechanisms were designed and added to the ant colony optimisation, to satisfy the above compound and complex constraints. The processing task chain was constructed using the rules of ant colony pheromone accumulation and a random search mechanism. The study designed a Gantt chart generation module to improve the usability and visibility of the program. Ultimately, through an actual case study of a complex box part including 73 processing elements and realising the design and planning of machining production lines that meet complex constraints by substituting algorithms, the balance rates of several groups of optimisation schemes were higher than 90%, which showed that the algorithm is effective and has a good economy and practicability. Full article
(This article belongs to the Special Issue Multi-Robot Systems and Their Applications)
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