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 November 2020.

Special Issue Editors

Dr. Juan Jesús Roldán Gómez
Website SciProfiles
Guest Editor
Autonomous University of Madrid, Francisco Tomás y Valiente, 11, 28049 Madrid, Spain.
Interests: robotics; multi-robot systems; swarms; adaptive and immersive interfaces; robotics in agriculture
Special Issues and Collections in MDPI journals
Prof. Dr. Antonio Barrientos
Website
Guest Editor
Technical University of Madrid - José Gutiérrez Abascal, 2, Madrid 28006, Spain
Interests: robotics; multi-robot systems; field robotics; robotics in agriculture; search and rescue robots
Special Issues and Collections in MDPI journals

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 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

  • 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 (16 papers)

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Open AccessArticle
Synchronization of Heterogeneous Multi-Robotic Cell with Emphasis on Low Computing Power
Appl. Sci. 2020, 10(15), 5165; https://doi.org/10.3390/app10155165 - 27 Jul 2020
Abstract
This paper presents a time-synchronization solution for operations performed by a heterogeneous set of robotic manipulators grouped into a production cell. The cell control is realized using master–slave architecture without an external control element. Information transmission in a cell is provided by a [...] Read more.
This paper presents a time-synchronization solution for operations performed by a heterogeneous set of robotic manipulators grouped into a production cell. The cell control is realized using master–slave architecture without an external control element. Information transmission in a cell is provided by a TCP/IP channel in which communication is ensured via sockets. The proposed problem solution includes an algorithm, which is verified and validated by simulation and tested in real environment. This algorithm requires minimal computational power thanks to an empirically oriented approach, which enables its processing directly by the control unit of each participating element of the robotic cell. The algorithm works on the basis of monitoring and evaluating time differences among sub-operations of master and slave devices. This ensures defined production cycle milestones of each robotic manipulator in the cell at the same time are attained. Dynamic speed adaptation of slave manipulators utilizing standard instructions of their native language is used. The proposed algorithm also includes a feedforward form of operations synchronization which responds to changes in the operating cycle of the master manipulator. The application of the solution proposal is supplemented with a visualization part. This part represents a complementary form of designed solution implementation. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Automatic Design of Collective Behaviors for Robots that Can Display and Perceive Colors
Appl. Sci. 2020, 10(13), 4654; https://doi.org/10.3390/app10134654 - 06 Jul 2020
Abstract
Research in swarm robotics has shown that automatic design is an effective approach to realize robot swarms. In automatic design methods, the collective behavior of a swarm is obtained by automatically configuring and fine-tuning the control software of individual robots. In this paper, [...] Read more.
Research in swarm robotics has shown that automatic design is an effective approach to realize robot swarms. In automatic design methods, the collective behavior of a swarm is obtained by automatically configuring and fine-tuning the control software of individual robots. In this paper, we present TuttiFrutti: an automatic design method for robot swarms that belongs to AutoMoDe—a family of methods that produce control software by assembling preexisting software modules via optimization. The peculiarity of TuttiFrutti is that it designs control software for e-puck robots that can display and perceive colors using their RGB LEDs and omnidirectional camera. Studies with AutoMoDe have been so far restricted by the limited capabilities of the e-pucks. By enabling the use of colors, we significantly enlarge the variety of collective behaviors they can produce. We assess TuttiFrutti with swarms of e-pucks that perform missions in which they should react to colored light. Results show that TuttiFrutti designs collective behaviors in which the robots identify the colored light displayed in the environment and act accordingly. The control software designed by TuttiFrutti endowed the swarms of e-pucks with the ability to use color-based information for handling events, communicating, and navigating. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Mixed Reality Simulation of High-Endurance Unmanned Aerial Vehicle with Dual-Head Electromagnetic Propulsion Devices for Earth and Other Planetary Explorations
Appl. Sci. 2020, 10(11), 3736; https://doi.org/10.3390/app10113736 - 28 May 2020
Abstract
One of the major limitations of existing unmanned aerial vehicles is limited flight endurance. In this study, we designed an innovative uninterrupted electromagnetic propulsion device for high-endurance missions of a quadcopter drone for the lucrative exploration of earth and other planets with atmospheres. [...] Read more.
One of the major limitations of existing unmanned aerial vehicles is limited flight endurance. In this study, we designed an innovative uninterrupted electromagnetic propulsion device for high-endurance missions of a quadcopter drone for the lucrative exploration of earth and other planets with atmospheres. As an airborne platform, this device could achieve scientific objectives better than state-of-the-art revolving spacecraft and walking robots, without any terrain limitation. We developed a mixed reality simulation based on a quadcopter drone and an X-Plane flight simulator. A computer with the X-Plane flight simulator represented the virtual part, and a real quadcopter operating within an airfield represented the real part. In the first phase of our study, we developed a connection interface between the X-Plane flight simulator and the quadcopter ground control station in MATLAB. The experimental results generated from the Earth’s atmosphere show that the flight data from the real and the virtual quadcopters are precise and very close to the prescribed target. The proof-of-concept of the mixed reality simulation of the quadcopter at the Earth atmosphere was verified and validated through several experimental flights of the F450 spider quadcopter with a Pixhawk flight controller with the restricted endurance at the airfield location of Hangang Drone Park in Seoul, South Korea. We concluded that the new generation drones integrated with lightweight electromagnetic propulsion devices are a viable option for achieving unrestricted flight endurance with improved payload capability for Earth and other planetary explorations with the aid of mixed reality simulation to meet the mission flight path demands. This study provides insight into mixed reality simulation aiming for Mars explorations and high-endurance missions in the Earth’s atmosphere with credibility using quadcopter drones regulated by dual-head electromagnetic propulsion devices. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning
Appl. Sci. 2020, 10(10), 3633; https://doi.org/10.3390/app10103633 - 24 May 2020
Cited by 1
Abstract
Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, [...] Read more.
Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Contingent Task and Motion Planning under Uncertainty for Human–Robot Interactions
Appl. Sci. 2020, 10(5), 1665; https://doi.org/10.3390/app10051665 - 01 Mar 2020
Abstract
Manipulation planning under incomplete information is a highly challenging task for mobile manipulators. Uncertainty can be resolved by robot perception modules or using human knowledge in the execution process. Human operators can also collaborate with robots for the execution of some difficult actions [...] Read more.
Manipulation planning under incomplete information is a highly challenging task for mobile manipulators. Uncertainty can be resolved by robot perception modules or using human knowledge in the execution process. Human operators can also collaborate with robots for the execution of some difficult actions or as helpers in sharing the task knowledge. In this scope, a contingent-based task and motion planning is proposed taking into account robot uncertainty and human–robot interactions, resulting a tree-shaped set of geometrically feasible plans. Different sorts of geometric reasoning processes are embedded inside the planner to cope with task constraints like detecting occluding objects when a robot needs to grasp an object. The proposal has been evaluated with different challenging scenarios in simulation and a real environment. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Twin-Robot Dialogue System with Robustness against Speech Recognition Failure in Human-Robot Dialogue with Elderly People
Appl. Sci. 2020, 10(4), 1522; https://doi.org/10.3390/app10041522 - 23 Feb 2020
Abstract
As agents, social robots are expected to increase opportunities for dialogue with the elderly. However, it is difficult to sustain a dialogue with an elderly user because speech recognition frequently fails during the dialogue. Here, to overcome this problem, regardless of speech recognition [...] Read more.
As agents, social robots are expected to increase opportunities for dialogue with the elderly. However, it is difficult to sustain a dialogue with an elderly user because speech recognition frequently fails during the dialogue. Here, to overcome this problem, regardless of speech recognition failure, we developed a question–answer–response dialogue model. In this model, a robot took initiative in the dialogue by asking the user various questions. Moreover, to improve user experience during dialogue, we extended the model such that two robots could participate in the dialogue. Implementing these features, we conducted a field trial in a nursing home to evaluate the twin-robot dialogue system. The average word error rate of speech recognition was 0.778. Despite the frequently high number of errors, participants talked for 14 min in a dialogue with two robots and felt slightly strange during the dialogue. Although we found no significant difference between a dialogue with one robot and that with two robots, the effect size of the difference in the dialogue time with one robot and that with two robots was medium (Cohen’s d = −0.519). The results suggested that the presence of two robots might likely encourage elderly people to sustain the talk. Our results will contribute to the design of social robots to engage in dialogues with the elderly. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Director Tools for Autonomous Media Production with a Team of Drones
Appl. Sci. 2020, 10(4), 1494; https://doi.org/10.3390/app10041494 - 21 Feb 2020
Abstract
This paper proposes a set of director tools for autonomous media production with a team of drones. There is a clear trend toward using drones for media production, and the director is the person in charge of the whole system from a production [...] Read more.
This paper proposes a set of director tools for autonomous media production with a team of drones. There is a clear trend toward using drones for media production, and the director is the person in charge of the whole system from a production perspective. Many applications, mainly outdoors, can benefit from the use of multiple drones to achieve multi-view or concurrent shots. However, there is a burden associated with managing all aspects in the system, such as ensuring safety, accounting for drone battery levels, navigating drones, etc. Even though there exist methods for autonomous mission planning with teams of drones, a media director is not necessarily familiar with them and their language. We contribute to close this gap between media crew and autonomous multi-drone systems, allowing the director to focus on the artistic part. In particular, we propose a novel language for cinematography mission description and a procedure to translate those missions into plans that can be executed by autonomous drones. We also present our director’s Dashboard, a graphical tool allowing the director to describe missions for media production easily. Our tools have been integrated into a real team of drones for media production and we show results of example missions. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Mapless Collaborative Navigation for a Multi-Robot System Based on the Deep Reinforcement Learning
Appl. Sci. 2019, 9(20), 4198; https://doi.org/10.3390/app9204198 - 09 Oct 2019
Abstract
Compared with the single robot system, a multi-robot system has higher efficiency and fault tolerance. The multi-robot system has great potential in some application scenarios, such as the robot search, rescue and escort tasks, and so on. Deep reinforcement learning provides a potential [...] Read more.
Compared with the single robot system, a multi-robot system has higher efficiency and fault tolerance. The multi-robot system has great potential in some application scenarios, such as the robot search, rescue and escort tasks, and so on. Deep reinforcement learning provides a potential framework for multi-robot formation and collaborative navigation. This paper mainly studies the collaborative formation and navigation of multi-robots by using the deep reinforcement learning algorithm. The proposed method improves the classical Deep Deterministic Policy Gradient (DDPG) to address the single robot mapless navigation task. We also extend the single-robot Deep Deterministic Policy Gradient algorithm to the multi-robot system, and obtain the Parallel Deep Deterministic Policy Gradient (PDDPG). By utilizing the 2D lidar sensor, the group of robots can accomplish the formation construction task and the collaborative formation navigation task. The experiment results in a Gazebo simulation platform illustrates that our method is capable of guiding mobile robots to construct the formation and keep the formation during group navigation, directly through raw lidar data inputs. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
SC-M*: A Multi-Agent Path Planning Algorithm with Soft-Collision Constraint on Allocation of Common Resources
Appl. Sci. 2019, 9(19), 4037; https://doi.org/10.3390/app9194037 - 26 Sep 2019
Cited by 1
Abstract
Multi-agent path planning (MAPP) is increasingly being used to address resource allocation problems in highly dynamic, distributed environments that involve autonomous agents. Example domains include surveillance automation, traffic control and others. Most MAPP approaches assume hard collisions, e.g., agents cannot share resources, or [...] Read more.
Multi-agent path planning (MAPP) is increasingly being used to address resource allocation problems in highly dynamic, distributed environments that involve autonomous agents. Example domains include surveillance automation, traffic control and others. Most MAPP approaches assume hard collisions, e.g., agents cannot share resources, or co-exist at the same node or edge. This assumption unnecessarily restricts the solution space and does not apply to many real-world scenarios. To mitigate this limitation, this paper introduces a more general class of MAPP problems—MAPP in a soft-collision context. In soft-collision MAPP problems, agents can share resources or co-exist in the same location at the expense of reducing the quality of the solution. Hard constraints can still be modeled by imposing a very high cost for sharing. This paper motivates and defines the soft-collision MAPP problem, and generalizes the widely-used M* MAPP algorithm to support the concept of soft-collisions. Soft-collision M* (SC-M*) extends M* by changing the definition of a collision, so paths with collisions that have a quality penalty below a given threshold are acceptable. For each candidate path, SC-M* keeps track of the reduction in satisfaction level of each agent using a collision score, and it places agents whose collision scores exceed its threshold into a soft-collision set for reducing the score. Our evaluation shows that SC-M* is more flexible and more scalable than M*. It can also handle complex environments that include agents requesting different types of resources. Furthermore, we show the benefits of SC-M* compared with several baseline algorithms in terms of path cost, success rate and run time. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
An Amalgamation of Hormone Inspired Arbitration Systems for Application in Robot Swarms
Appl. Sci. 2019, 9(17), 3524; https://doi.org/10.3390/app9173524 - 27 Aug 2019
Abstract
Previous work has shown that virtual hormone systems can be engineered to arbitrate swarms of robots between sets of behaviours. These virtual hormones act similarly to their natural counterparts, providing a method of online, reactive adaptation. It is yet to be shown how [...] Read more.
Previous work has shown that virtual hormone systems can be engineered to arbitrate swarms of robots between sets of behaviours. These virtual hormones act similarly to their natural counterparts, providing a method of online, reactive adaptation. It is yet to be shown how virtual hormone systems could be used when a robotic swarm has a large variety of task types to execute. This paper details work that demonstrates the viability of a collection of virtual hormones that can be used to regulate and adapt a swarm over time, in response to different environments and tasks. Specifically, the paper examines a new method of hormone speed control for energy efficiency and combines it with two existing systems controlling environmental preference as well as a selection of behaviours that produce an effective foraging swarm. Experiments confirm the effectiveness of the combined system, showing that a swarm of robots equipped with multiple virtual hormones can forage efficiently to a specified item demand within an allotted period of time. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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Open AccessArticle
Development of an Effective Information Media Using Two Android Robots
Appl. Sci. 2019, 9(17), 3442; https://doi.org/10.3390/app9173442 - 21 Aug 2019
Cited by 1
Abstract
Conversational robots have been used to convey information to people in the real world. Android robots, which have a human-like appearance, are expected to be able to convey not only objective information but also subjective information, such as a robot’s feelings. Meanwhile, as [...] Read more.
Conversational robots have been used to convey information to people in the real world. Android robots, which have a human-like appearance, are expected to be able to convey not only objective information but also subjective information, such as a robot’s feelings. Meanwhile, as an approach to realize attractive conversation, multi-party conversation by multiple robots was the focus of this study. By collaborating among several robots, the robots provide information while maintaining the naturalness of conversation. However, the effectiveness of interaction with people has not been surveyed using this method. In this paper, to develop more efficient media to convey information, we propose a scenario-based, semi-passive conversation system using two androids. To verify its effectiveness, we conducted a subjective experiment comparing it to a system that does not include any interaction with people, and we investigated how much information the proposed system successfully conveys by using a recall test and a questionnaire about the conversation and androids. The experimental results showed that participants who engaged with the proposed system recalled more content from the conversation and felt more empathic concern for androids. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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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 - 08 Jul 2019
Cited by 2
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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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 - 29 Jun 2019
Cited by 2
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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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 - 03 Mar 2019
Cited by 3
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 - 09 Feb 2019
Cited by 3
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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Review

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Open AccessReview
Engineering Challenges Ahead for Robot Teamwork in Dynamic Environments
Appl. Sci. 2020, 10(4), 1368; https://doi.org/10.3390/app10041368 - 18 Feb 2020
Abstract
The increasing number of robots around us creates a demand for connecting these robots in order to achieve goal-driven teamwork in heterogeneous multi-robot systems. In this paper, we focus on robot teamwork specifically in dynamic environments. While the conceptual modeling of multi-agent teamwork [...] Read more.
The increasing number of robots around us creates a demand for connecting these robots in order to achieve goal-driven teamwork in heterogeneous multi-robot systems. In this paper, we focus on robot teamwork specifically in dynamic environments. While the conceptual modeling of multi-agent teamwork was studied extensively during the last two decades and commercial multi-agent applications were built based on the theoretical foundations, the steadily increasing use of autonomous robots in many application domains gave the topic new significance and shifted the focus more toward engineering concerns for multi-robot systems. From a distributed systems perspective, we discuss general engineering challenges that apply to robot teamwork in dynamic application domains and review state-of-the-art solution approaches for these challenges. This leads us to open research questions that need to be tackled in future work. Full article
(This article belongs to the Special Issue Multi-Robot Systems: Challenges, Trends and Applications)
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