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Collective Mobile Robotics: From Theory to Real-World Applications
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Collective Mobile Robotics: From Theory to Real-World Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 4596

Special Issue Editor

Prof. Dr. Frédéric Guinand

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Guest Editor
Laboratoire d’Informatique, du Traitement de l’Information et des Systéme (LITIS), Faculty of Science and Technology, Normandie University, 76600 Le Harve, France
Interests: swarm robotics; dynamic graphs / complex networks; nature-inspired computing; distributed and parallel algorithms; mobile Ad Hoc networking; bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

From theoretical models to deployment of real robots, Collective Mobile Robotics (CMR) have witnessed a growing interest last two decades. In the context of this special issue, a swarm is considered as a set of autonomous machines presenting a collective behavior without relying on any centralized mechanism. This special issue aims at offering a venue for specialists of any domain related to robot swarming, from theoretical foundations to real-world applications including robotic platforms and testbeds. Measuring the distance that may exist between theory and practical experiments, and raising open questions related to swarm robotics is one of the objectives of this SI. Contributions of mature works as well as emerging new ideas from theoretical models to existing hardware solutions enabling robots to behave as swarms are welcome. More generally, topics of interest for this special issue include (but are not limited to) the following topics :

  • Theoretical Models (e.g. Look-Compute-Move, graph-based models)
  • Distributed Algorithms
  • Cooperation versus Competition
  • Bio-Inspired Approaches
  • Communication issues
  • Optimization, Robustness, Fault Tolerance and Resilience
  • Simulations
  • Pattern Formation
  • Environment Perception
  • Technological Hardware/Software Solutions and Platforms
  • Collective Environment Perception
  • Human - CMR interactions
  • Applications

Prof. Dr. Frédéric Guinand
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. Sensors 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 2600 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

29 pages, 5715 KiB  
Article
Decentralized Coordination of a Multi-UAV System for Spatial Planar Shape Formations
by Etienne Petitprez, François Guérin, Frédéric Guinand, Florian Germain and Nicolas Kerthe
Sensors 2023, 23(23), 9553; https://doi.org/10.3390/s23239553 - 01 Dec 2023
Viewed by 714
Abstract
Motivated by feedback from firefighters in Normandy, this work aims to provide a simple technique for a set of identical drones to collectively describe an arbitrary planar virtual shape in a 3D space in a decentralized manner. The original problem involved surrounding a [...] Read more.
Motivated by feedback from firefighters in Normandy, this work aims to provide a simple technique for a set of identical drones to collectively describe an arbitrary planar virtual shape in a 3D space in a decentralized manner. The original problem involved surrounding a toxic cloud to monitor its composition and short-term evolution. In the present work, the pattern is described using Fourier descriptors, a convenient mathematical formulation for that purpose. Starting from a reference point, which can be the center of a fire, Fourier descriptors allow for more precise description of a shape as the number of harmonics increases. This pattern needs to be evenly occupied by the fleet of drones under consideration. To optimize the overall view, the drones must be evenly distributed angularly along the shape. The proposed method enables virtual planar shape description, decentralized bearing angle assignment, drone movement from takeoff positions to locations along the shape, and collision avoidance. Furthermore, the method allows for the number of drones to change during the mission. The method has been tested both in simulation, through emulation, and in outdoor experiments with real drones. The obtained results demonstrate that the method is applicable in real-world contexts. Full article
(This article belongs to the Special Issue Collective Mobile Robotics: From Theory to Real-World Applications)
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24 pages, 3072 KiB  
Article
Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas
by Matheus Nohra Haddad, Andréa Cynthia Santos, Christophe Duhamel and Amadeu Almeida Coco
Sensors 2023, 23(23), 9540; https://doi.org/10.3390/s23239540 - 30 Nov 2023
Viewed by 1306
Abstract
This study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are [...] Read more.
This study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between destinations, with an associated weight, corresponding to the battery consumption to fly to a location. In addition, in the DSRP addressed here, a set of drones are deployed in a cooperative drone swarms approach to boost the search. In this context, a V-shaped formation is applied with leader replacements, which allows energy saving. We propose a computation model for the DSRP that considers each drone as an agent that selects the next search location to visit through a simple and efficient method, the Drone Swarm Heuristic. In order to evaluate the proposed model, scenarios based on the Beirut port explosion in 2020 are used. Numerical experiments are presented in the offline and online versions of the proposed method. The results from such scenarios showed the efficiency of the proposed approach, attesting not only the coverage capacity of the computational model but also the advantage of adopting the V-shaped formation flight with leader replacements. Full article
(This article belongs to the Special Issue Collective Mobile Robotics: From Theory to Real-World Applications)
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22 pages, 8488 KiB  
Article
Swarm Metaverse for Multi-Level Autonomy Using Digital Twins
by Hung Nguyen, Aya Hussein, Matthew A. Garratt and Hussein A. Abbass
Sensors 2023, 23(10), 4892; https://doi.org/10.3390/s23104892 - 19 May 2023
Cited by 1 | Viewed by 1918
Abstract
Robot swarms are becoming popular in domains that require spatial coordination. Effective human control over swarm members is pivotal for ensuring swarm behaviours align with the dynamic needs of the system. Several techniques have been proposed for scalable human–swarm interaction. However, these techniques [...] Read more.
Robot swarms are becoming popular in domains that require spatial coordination. Effective human control over swarm members is pivotal for ensuring swarm behaviours align with the dynamic needs of the system. Several techniques have been proposed for scalable human–swarm interaction. However, these techniques were mostly developed in simple simulation environments without guidance on how to scale them up to the real world. This paper addresses this research gap by proposing a metaverse for scalable control of robot swarms and an adaptive framework for different levels of autonomy. In the metaverse, the physical/real world of a swarm symbiotically blends with a virtual world formed from digital twins representing each swarm member and logical control agents. The proposed metaverse drastically decreases swarm control complexity due to human reliance on only a few virtual agents, with each agent dynamically actuating on a sub-swarm. The utility of the metaverse is demonstrated by a case study where humans controlled a swarm of uncrewed ground vehicles (UGVs) using gestural communication, and via a single virtual uncrewed aerial vehicle (UAV). The results show that humans could successfully control the swarm under two different levels of autonomy, while task performance increases as autonomy increases. Full article
(This article belongs to the Special Issue Collective Mobile Robotics: From Theory to Real-World Applications)
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