Special Issue "Multi-Robot Systems: Challenges, Trends and Applications"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 30 June 2020.

Special Issue Editors

Guest Editor
Dr. Juan Jesús Roldán Gómez

Technical University of Madrid - José Gutiérrez Abascal, 2, Madrid 28006, Spain
Website | E-Mail
Interests: robotics; multi-robot systems; swarms; adaptive and immersive interfaces; robotics in agriculture
Guest Editor
Prof. Dr. Antonio Barrientos

Technical University of Madrid - José Gutiérrez Abascal, 2, Madrid 28006, Spain
Website | E-Mail
Interests: robotics; multi-robot systems; field robotics; robotics in agriculture; search and rescue robots

Special Issue Information

Dear Colleagues,

We are proud to announce this Special Issue on “Multi-Robot Systems: Challenges, Trends and Applications”.

Multi-Robot Systems (MRS) have emerged as a suitable alternative to single robots, since they can be more efficient, flexible and fault tolerant. However, the complexity of these systems poses some challenges at the time of their deployment, control and recovery. In particular, three human factor issues are especially relevant: Operator workload, situational awareness and stress.

This Special Issue aims at collecting a set of high-quality works that address the challenges of MRS (e.g., mission planning, human-robot interaction and operator interfaces) and/or apply these systems to interesting applications (security, environmental monitoring, agriculture, search and rescue, etc.).

We will be glad to receive papers with state-of-the-art reviews, original research and real-world applications.

Please contact us if you have any doubts regarding your submission.

Best regards,

Dr. Juan Jesús Roldán Gómez
Prof. Dr. Antonio Barrientos
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 papers will be 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 1500 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

  • Multi-robot systems: heterogeneous and homogeneous fleets
  • Multi-robot mission planning, modeling and optimization
  • From multi-robot systems to robot swarms
  • Human factor issues: workload, situational awareness, stress...
  • Human-robot interaction: collaboration and teaming
  • Operator Interfaces: adaptation and immersion
  • Applications: search and rescue, environmental monitoring…

Published Papers (4 papers)

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Research

Open AccessArticle
On Sharing Spatial Data with Uncertainty Integration Amongst Multiple Robots Having Different Maps
Appl. Sci. 2019, 9(13), 2753; https://doi.org/10.3390/app9132753
Received: 30 May 2019 / Revised: 3 July 2019 / Accepted: 4 July 2019 / Published: 8 July 2019
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Abstract
Information sharing is a powerful feature of multi-robot systems. Sharing information precisely and accurately is important and has many benefits. Particularly, smart information sharing can improve robot path planning. If a robot finds a new obstacle or blocked path, it can share this [...] Read more.
Information sharing is a powerful feature of multi-robot systems. Sharing information precisely and accurately is important and has many benefits. Particularly, smart information sharing can improve robot path planning. If a robot finds a new obstacle or blocked path, it can share this information with other remote robots allowing them to plan better paths. However, there are two problems with such information sharing. First, the maps of the robots may be different in nature (e.g., 2D grid-map, 3D semantic map, feature map etc.) as the sensors used by the robots for mapping and localization may be different. Even the maps generated using the same sensor (e.g., Lidar) can vary in scale or rotation and the sensors used might have different specifications like resolution or range. In such scenarios, the ‘correspondence problem’ in different maps is a critical bottleneck in information sharing. Second, the transience of the obstacles has to be considered while also considering the positional uncertainty of the new obstacles while sharing information. In our previous work, we proposed a ‘node-map’ with a confidence decay mechanism to solve this problem. However, the previous work had many limitations due to the decoupling of new obstacle’s positional uncertainty and confidence decay. Moreover, the previous work applied only to homogeneous maps. In addition, the previous model worked only with static obstacles in the environment. The current work extends our previous work in three main ways: (1) we extend the previous work by integrating positional uncertainty in the confidence decay mechanism and mathematically model the transience of newly added or removed obstacles and discuss its merits; (2) we extend the previous work by considering information sharing in heterogeneous maps build using different sensors; and (3) we consider dynamic obstacles like moving people in the environment and test the proposed method in complex scenarios. All the experiments are performed in real environments and with actual robots and results are discussed. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Graphical abstract

Open AccessArticle
Robust Visual-Aided Autonomous Takeoff, Tracking, and Landing of a Small UAV on a Moving Landing Platform for Life-Long Operation
Appl. Sci. 2019, 9(13), 2661; https://doi.org/10.3390/app9132661
Received: 31 May 2019 / Revised: 16 June 2019 / Accepted: 25 June 2019 / Published: 29 June 2019
PDF Full-text (11403 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Robot cooperation is key in Search and Rescue (SaR) tasks. Frequently, these tasks take place in complex scenarios affected by different types of disasters, so an aerial viewpoint is useful for autonomous navigation or human tele-operation. In such cases, an Unmanned Aerial Vehicle [...] Read more.
Robot cooperation is key in Search and Rescue (SaR) tasks. Frequently, these tasks take place in complex scenarios affected by different types of disasters, so an aerial viewpoint is useful for autonomous navigation or human tele-operation. In such cases, an Unmanned Aerial Vehicle (UAV) in cooperation with an Unmanned Ground Vehicle (UGV) can provide valuable insight into the area. To carry out its work successfully, such as multi-robot system requires the autonomous takeoff, tracking, and landing of the UAV on the moving UGV. Furthermore, it needs to be robust and capable of life-long operation. In this paper, we present an autonomous system that enables a UAV to take off autonomously from a moving landing platform, locate it using visual cues, follow it, and robustly land on it. The system relies on a finite state machine, which together with a novel re-localization module allows the system to operate robustly for extended periods of time and to recover from potential failed landing maneuvers. Two approaches for tracking and landing are developed, implemented, and tested. The first variant is based on a novel height-adaptive PID controller that uses the current position of the landing platform as the target. The second one combines this height-adaptive PID controller with a Kalman filter in order to predict the future positions of the platform and provide them as input to the PID controller. This facilitates tracking and, mainly, landing. Both the system as a whole and the re-localization module in particular have been tested extensively in a simulated environment (Gazebo). We also present a qualitative evaluation of the system on the real robotic platforms, demonstrating that our system can also be deployed on real robotic platforms. For the benefit of the community, we make our software open source. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Figure 1

Open AccessArticle
Unscented Transformation-Based Multi-Robot Collaborative Self-Localization and Distributed Target Tracking
Appl. Sci. 2019, 9(5), 903; https://doi.org/10.3390/app9050903
Received: 26 December 2018 / Revised: 11 February 2019 / Accepted: 27 February 2019 / Published: 3 March 2019
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Abstract
The problem of multi-robot collaborative self-localization and distributed target tracking in practical scenarios is studied in this work. The major challenge in solving the problem in a distributed fashion is properly dealing with inter-robot and robot–target correlations in order to realize consistent state [...] Read more.
The problem of multi-robot collaborative self-localization and distributed target tracking in practical scenarios is studied in this work. The major challenge in solving the problem in a distributed fashion is properly dealing with inter-robot and robot–target correlations in order to realize consistent state estimates of the local robots and the target simultaneously. In this paper, an unscented transformation-based collaborative self-localization and target tracking algorithm is proposed. Inter-robot correlations are approximated in a distributed fashion, and robot–target correlations are safely discarded with a conservative covariance intersection method. Furthermore, the state update is realized in an asynchronous manner with different kinds of measurements while accounting for measurement and communication limitations. Finally, to deal with nonlinearity in the processes and measurement models, the unscented transformation approach is adopted. Unscented transformation is better able to characterize nonlinearity than the extended Kalman filter-based method and does not require computation of the Jacobian matrix. Simulations are extensively studied to show that the proposed method can realize stable state estimates of both local robots and targets, and results show that it outperforms the EKF-based method. Moreover, the effectiveness of the proposed method is verified on experimental quadrotor platforms carrying off-the-shelf onboard sensors. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
An Auto-Adaptive Multi-Objective Strategy for Multi-Robot Exploration of Constrained-Communication Environments
Appl. Sci. 2019, 9(3), 573; https://doi.org/10.3390/app9030573
Received: 21 December 2018 / Revised: 31 January 2019 / Accepted: 2 February 2019 / Published: 9 February 2019
Cited by 1 | PDF Full-text (1199 KB) | HTML Full-text | XML Full-text
Abstract
The exploration problem is a fundamental subject in autonomous mobile robotics that deals with achieving the complete coverage of a previously unknown environment. There are several scenarios where completing exploration of a zone is a main part of the mission. Due to the [...] Read more.
The exploration problem is a fundamental subject in autonomous mobile robotics that deals with achieving the complete coverage of a previously unknown environment. There are several scenarios where completing exploration of a zone is a main part of the mission. Due to the efficiency and robustness brought by multi-robot systems, exploration is usually done cooperatively. Wireless communication plays an important role in collaborative multi-robot strategies. Unfortunately, the assumption of stable communication and end-to-end connectivity may be easily compromised in real scenarios. In this paper, a novel auto-adaptive multi-objective strategy is followed to support the selection of tasks regarding both exploration performance and connectivity level. Compared with others, the proposed approach shows effectiveness and flexibility to tackle the multi-robot exploration problem, being capable of decreasing the last of disconnection periods without noticeable degradation of the completion exploration time. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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