Multi-Robot Systems: From Theoretical Contributions to Practical Applications

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

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 11763

Special Issue Editors


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Guest Editor
Division of Systems and Automatic Control, Department of Electrical and Computer Engineering, University of Patras, Greece
Interests: Prescribed performance control; Multi-agent systems; Robotics
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Guest Editor
Deptartment of Mechanical Engineering, National Technical University of Athens, 15780 Zografos, Greece
Interests: control of ground and aerial vehicles; single- and multi-agent motion planning; artificial potential fields; model predictive control

Special Issue Information

Dear Colleagues,

During the last decades, a considerable amount of research has been focused on the design and control of multi-robot systems, improving our everyday lives owing to their adaptability and multi-functionality. Critical missions with strict specifications in terms of accuracy, dexterity, and speed of completion are almost impossible to be fulfilled by the deployment of a single robot. Moreover, the risk of mission failure in a standalone approach is significantly high due to possible critical sensor or actuation faults. Instead, the deployment of multiple robots may significantly speed up the task completion, improve the perception, and strengthen the fault tolerance capabilities of the overall system. Unfortunately, however, the centralized approach to multi-robot operation, in which a single unit has access to every robot’s local information and issues commands to them, is not robust to faults and does not scale well as the number of robots increases. Alternatively, distributed multi-robot control, which allows a group of robots subject to potentially limited sensing and communication capabilities to achieve global tasks without the intervention of a central controller or access to global information, has been rapidly advancing, proving its true potential through various applications. Examples of such applications can be found in multi-robot surveillance, planetary exploration, search and rescue missions, service robots in smart homes and offices, warehouse management, transportation, etc.

This Special Issue aims at boosting multi-robot systems research and seeks articles that focus on the state-of-the-art research in all aspects of multi-robot systems. While work based on real robots is preferable, we will also accept work based on simulation only. The topics of interest for this Special Issue include, but are not limited to:

  • Distributed coordination and cooperation in multi-robot systems;
  • Distributed cooperative perception;
  • Distributed control and planning;
  • Machine learning in multi-robot systems;
  • Mapping, localization, and navigation in multi-robot systems;
  • Physical interaction in/with multi-robot systems.

Dr. Charalampos P. Bechlioulis
Dr. Panagiotis Vlantis
Guest Editors

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Published Papers (3 papers)

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Research

28 pages, 37079 KiB  
Article
Design of a Rapid Structure from Motion (SfM) Based 3D Reconstruction Framework Using a Team of Autonomous Small Unmanned Aerial Systems (sUAS)
by Douglas Shane Smith, Jr. and Hakki Erhan Sevil
Robotics 2022, 11(5), 89; https://doi.org/10.3390/robotics11050089 - 4 Sep 2022
Cited by 2 | Viewed by 2629
Abstract
The aim of this research effort was to develop a framework for a structure from motion (SfM)-based 3D reconstruction approach with a team of autonomous small unmanned aerial systems (sUASs) using a distributed behavior model. The framework is composed of two major goals [...] Read more.
The aim of this research effort was to develop a framework for a structure from motion (SfM)-based 3D reconstruction approach with a team of autonomous small unmanned aerial systems (sUASs) using a distributed behavior model. The framework is composed of two major goals to accomplish this: a distributed behavior model for a team of sUASs and a SfM-based 3D reconstruction using team of sUASs. The developed distributed behavior model is based on the entropy of the system, and when the entropy of the system is high, the sUASs get closer to reducing the overall entropy. This is called the grouping phase. If the entropy is less than the predefined threshold, then the sUASs switch to the 3D reconstruction phase. The novel part of the framework is that sUASs are only given the object of interest to reconstruct the 3D model, and they use the developed distributed behavior to coordinate their motion for that goal. A comprehensive parameter analysis was performed, and optimum sets of parameters were selected for each sub-system. Finally, optimum parameters for two sub-systems were combined in a simulation to demonstrate the framework’s operability and evaluate the completeness and speed of the reconstructed model. The simulation results show that the framework operates successfully and is capable of generating complete models as desired, autonomously. Full article
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15 pages, 1373 KiB  
Article
Swarm Crawler Robots Using Lévy Flight for Targets Exploration in Large Environments
by Yoshiaki Katada, Sho Hasegawa, Kaito Yamashita, Naoki Okazaki and Kazuhiro Ohkura
Robotics 2022, 11(4), 76; https://doi.org/10.3390/robotics11040076 - 22 Jul 2022
Cited by 10 | Viewed by 3125
Abstract
This study tackles the task of swarm robotics, where robots explore the environment to detect targets. When a robot detects a target, the robot must be connected with a base station via intermediate relay robots for wireless communication. Our previous results confirmed that [...] Read more.
This study tackles the task of swarm robotics, where robots explore the environment to detect targets. When a robot detects a target, the robot must be connected with a base station via intermediate relay robots for wireless communication. Our previous results confirmed that Lévy flight outperformed the usual random walk for exploration strategy in an indoor environment. This paper investigated the search performance of swarm crawler robots with Lévy flight on target detection problems in large environments through a series of real robots’ experiments. The results suggest that the swarm crawler robots with Lévy flight succeeded in the target’s discovery in the indoor environment with a 100% success rate, and were able to find several targets in a given time in the outdoor environment. Thus, we confirmed that target exploration in a large environment would be possible by crawler robots with Lévy flight and significant variances in the detection rate among the positions to detect the outdoor environment’s target. Full article
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23 pages, 4909 KiB  
Article
Coordination of Multiple Robotic Vehicles in Obstacle-Cluttered Environments
by Charalampos P. Bechlioulis, Panagiotis Vlantis and Kostas J. Kyriakopoulos
Robotics 2021, 10(2), 75; https://doi.org/10.3390/robotics10020075 - 22 May 2021
Cited by 4 | Viewed by 4631
Abstract
In this work, we consider the motion control problem for a platoon of unicycle robots operating within an obstacle-cluttered workspace. Each robot is equipped with a proximity sensor that allows it to perceive nearby obstacles as well as a camera to obtain its [...] Read more.
In this work, we consider the motion control problem for a platoon of unicycle robots operating within an obstacle-cluttered workspace. Each robot is equipped with a proximity sensor that allows it to perceive nearby obstacles as well as a camera to obtain its relative position with respect to its preceding robot. Additionally, no robot other than the leader of the team is able to localize itself within the workspace and no centralized communication network exists, i.e., explicit information exchange between the agents is unavailable. To tackle this problem, we adopt a leader–follower architecture and propose a novel, decentralized control law for each robot-follower, based on the Prescribed Performance Control method, which guarantees collision-free tracking and visual connectivity maintenance by ensuring that each follower maintains its predecessor within its camera field of view while keeping static obstacles out of the line of sight for all time. Finally, we verify the efficacy of the proposed control scheme through extensive simulations. Full article
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