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Robotics
Special Issues
The State of the Art of Swarm Robotics
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The State of the Art of Swarm Robotics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "AI in Robotics".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 7738

Special Issue Editors

Prof. Dr. Goldie Nejat

E-Mail Website
Guest Editor
Autonomous Systems and Biomechatronics Laboratory, Mechanical and Industrial Engineering Department, University of Toronto, Toronto, ON M5S 3E3, Canada
Interests: intelligent assistive/service robots; human-robot interactions; semi-autonomous / autonomous control
Prof. Dr. Beno Benhabib

E-Mail Website
Guest Editor
Computer Integrated Manufacturing Laboratory (CIMLab), University of Toronto, Toronto, ON M5S 3G8, Canada
Interests: design and control of intelligent autonomous systems

Special Issue Information

Dear Colleagues,

Swarm robotic systems are large teams of small, simple, and collaborative robots, implemented with the aim of replacing traditional small teams of large and sophisticated robots. The use of such large teams of simple robots promotes both robustness to environmental disturbances and failure of robot components, as well as flexibility in their application to real-world problems that may be inaccessible to larger robots. Swarm robotics has recently received increased attention due to advances and miniaturization in sensing, processing, communication, and manipulation technologies. Furthermore, they have been proposed for and used in a variety of industries, such as agriculture, environmental monitoring, and entertainment.

While the simplicity of the robots used in a swarm provides the benefits detailed above, it also increases the difficulty of controlling them. Technologies used in swarm robotics typically restrict an individual swarm robot solely to local information about its neighbors and environment. As such, the methodologies developed for traditional robotic systems cannot simply be transferred to a swarm, and swarm-specific approaches are necessary for their autonomous and semi-autonomous control. The goal of this Special Issue is thus to provide an opportunity to present state-of-the-art contributions in swarm robotics that address problems including but not limited to swarm perception, communication, localization, mapping, motion planning, motion control, human–swarm interactions, simulation platforms, and robotic platforms.

Prof. Dr. Goldie Nejat
Prof. Dr. Beno Benhabib
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. Robotics is an international peer-reviewed open access monthly 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 1800 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.

Keywords

  • human–swarm interactions
  • swarm collective perception
  • distributed sensing
  • networked communication
  • swarm robotic applications
  • simulation platforms for large-scale swarms
  • swarm robot physical platforms
  • swarm localization
  • swarm motion-planning
  • swarm task-allocation
  • swarm mapping
  • decentralized control

Published Papers (2 papers)

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Research

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29 pages, 7249 KiB  
Article
Occupancy Grid Mapping via Resource-Constrained Robotic Swarms: A Collaborative Exploration Strategy
by Andrew Rogers, Kasra Eshaghi, Goldie Nejat and Beno Benhabib
Robotics 2023, 12(3), 70; https://doi.org/10.3390/robotics12030070 - 09 May 2023
Cited by 1 | Viewed by 1968
Abstract
This paper addresses the problem of building an occupancy grid map of an unknown environment using a swarm comprising resource-constrained robots, i.e., robots with limited exteroceptive and inter-robot sensing capabilities. Past approaches have, commonly, used random-motion models to disperse the swarm and explore [...] Read more.
This paper addresses the problem of building an occupancy grid map of an unknown environment using a swarm comprising resource-constrained robots, i.e., robots with limited exteroceptive and inter-robot sensing capabilities. Past approaches have, commonly, used random-motion models to disperse the swarm and explore the environment randomly, which do not necessarily consider prior information already contained in the map. Herein, we present a collaborative, effective exploration strategy that directs the swarm toward ‘promising’ frontiers by dividing the swarm into two teams: landmark robots and mapper robots, respectively. The former direct the latter, toward promising frontiers, to collect proximity measurements to be incorporated into the map. The positions of the landmark robots are optimized to maximize new information added to the map while also adhering to connectivity constraints. The proposed strategy is novel as it decouples the problem of directing the resource-constrained swarm from the problem of mapping to build an occupancy grid map. The performance of the proposed strategy was validated through extensive simulated experiments. Full article
(This article belongs to the Special Issue The State of the Art of Swarm Robotics)
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Review

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24 pages, 14295 KiB  
Review
A Survey on Open-Source Simulation Platforms for Multi-Copter UAV Swarms
by Ziming Chen, Jinjin Yan, Bing Ma, Kegong Shi, Qiang Yu and Weijie Yuan
Robotics 2023, 12(2), 53; https://doi.org/10.3390/robotics12020053 - 01 Apr 2023
Cited by 1 | Viewed by 5108
Abstract
Simulation platforms are critical and indispensable tools for application developments of unmanned aerial vehicles (UAVs) because the UAVs are generally costly, have certain requirements for the test environment, and need professional licensed operators. Thus, developers prefer (or have) to test their applications on [...] Read more.
Simulation platforms are critical and indispensable tools for application developments of unmanned aerial vehicles (UAVs) because the UAVs are generally costly, have certain requirements for the test environment, and need professional licensed operators. Thus, developers prefer (or have) to test their applications on simulation platforms before implementing them on real machines. In the past decades, a considerable number of simulation platforms for robots have been developed, which brings convenience to developers, but also makes them hard to choose a proper one as they are not always familiar with all the features of platforms. To alleviate this dilemma, this paper provides a survey of open-source simulation platforms and employs the simulation of a multi-copter UAV swarm as an example. The survey covers seven widely used simulators, including Webots, Gazebo, CoppeliaSim, ARGoS, MRDS, MORSE, and USARSim. The paper outlines the requirements for multi-copter UAV swarms and shows how to select an appropriate platform. Additionally, the paper presents a case study of a UAV swarm based on Webots. This research will be beneficial to researchers, developers, educators, and engineers who seek suitable simulation platforms for application development, (not only multi-copter UAV swarms but also other types of robots), which further helps them to save expenses for testing, and speed up development progress. Full article
(This article belongs to the Special Issue The State of the Art of Swarm Robotics)
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