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Electronics
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Autonomous Navigation Systems: Design, Control and Applications
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Autonomous Navigation Systems: Design, Control and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (10 March 2021) | Viewed by 20354

Special Issue Editors

Prof. Dr. Rafael Casado

E-Mail Website
Guest Editor
Department of Computing Systems, University of Castilla-La Mancha, 02071 Albacete, Spain
Interests: control systems; autonomous navigation systems; unmanned aerial vehicles; air navigation and air traffic management systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Aurelio Bermúdez

E-Mail Website
Guest Editor
Department of Computing Systems, University of Castilla-La Mancha, 02071 Albacete, Spain
Interests: autonomous navigation systems; unmanned aerial vehicles; air navigation and air traffic management systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

 In a few years, advances in autonomous navigation systems (ANS) will allow all kinds of robots to travel everywhere, interacting among them and/or with humans. Potential applications are innumerable and some, so far, unimaginable.

Producing truly reliable ANS systems goes beyond overcoming a series of technological challenges, ranging from the production of better sensors and actuators to the development of algorithms and interaction protocols that allow robots to make successful navigation decisions.

This Special Issue focuses on the analysis, design, implementation and emerging applications of Autonomous Navigation Systems. We invite the scientific community to provide high-quality contributions with consolidated and evaluated research related to this promising investigation area. 

The topics of interest include, but are not limited to:

  • Autonomous mobile robots
  • Sensing and perception for navigation purposes (GPS, IMU, INS, LIDAR, odometry, camera…)
  • Simultaneous localization and mapping (SLAM)
  • Path planning, following, and tracking
  • Obstacle avoidance
  • Collision-free multi agent/robot navigation
  • Cooperative/swarm navigation
  • Human detection and interaction
  • Autonomous aerial vehicles
  • Autonomous underwater vehicles
  • Applications of autonomous mobile robots (industry, education, health, transportation, disaster management, space exploration, precision agriculture…)
  • Competitions of autonomous robotic platforms

Prof. Dr. Rafael Casado
Prof. Dr. Aurelio Bermúdez
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. Electronics 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 2400 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

  • Autonomous mobile robots
  • Simultaneous localization and mapping (SLAM)
  • Path planning and following
  • Collision-free multi agent/robot navigation
  • Cooperative/swarm navigation
  • Human detection and interaction
  • Autonomous aerial/underwater vehicles

Published Papers (6 papers)

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Research

18 pages, 685 KiB  
Article
Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies
by Anum Mushtaq, Irfan ul Haq, Wajih un Nabi, Asifullah Khan and Omair Shafiq
Electronics 2021, 10(10), 1221; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10101221 - 20 May 2021
Cited by 12 | Viewed by 3247
Abstract
Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps [...] Read more.
Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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19 pages, 4076 KiB  
Article
Map Merging with Suppositional Box for Multi-Robot Indoor Mapping
by Baifan Chen, Siyu Li, Haowu Zhao and Limei Liu
Electronics 2021, 10(7), 815; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10070815 - 30 Mar 2021
Cited by 10 | Viewed by 2130
Abstract
For the map building of unknown indoor environment, compared with single robot, multi-robot collaborative mapping has higher efficiency. Map merging is one of the fundamental problems in multi-robot collaborative mapping. However, in the process of grid map merging, image processing methods such as [...] Read more.
For the map building of unknown indoor environment, compared with single robot, multi-robot collaborative mapping has higher efficiency. Map merging is one of the fundamental problems in multi-robot collaborative mapping. However, in the process of grid map merging, image processing methods such as feature matching, as a basic method, are challenged by low feature matching rate. Driven by this challenge, a novel map merging method based on suppositional box that is constructed by right-angled points and vertical lines is proposed. The paper firstly extracts right-angled points of suppositional box selected from the vertical point which is the intersection of the vertical line. Secondly, based on the common edge characteristics between the right-angled points, suppositional box in the map is constructed. Then the transformation matrix is obtained according to the matching pair of suppositional boxes. Finally, for matching errors based on the length of pairs, Kalman filter is used to optimize the transformation matrix. Experimental results show that this method can effectively merge map in different scenes and the successful matching rate is greater than that of other features. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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31 pages, 57911 KiB  
Article
Comparative Study of Optimal Multivariable LQR and MPC Controllers for Unmanned Combat Air Systems in Trajectory Tracking
by Alvaro Ortiz, Sergio Garcia-Nieto and Raul Simarro
Electronics 2021, 10(3), 331; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10030331 - 01 Feb 2021
Cited by 8 | Viewed by 3233
Abstract
Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying [...] Read more.
Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying to satisfy a set of requirements that are sometimes in opposition. The purpose of this article was to compare two different control strategies in conjunction with a path-planning and guidance system with the objective of completing military missions in the most satisfactory way. For this purpose, a novel dynamic trajectory-planning algorithm is employed, which can obtain an appropriate trajectory by analyzing the environment as a discrete 3D adaptive mesh and performs a softening process a posteriori. Moreover, two multivariable control techniques are proposed, i.e., the linear quadratic regulator and the model predictive control, which were designed to offer optimal responses in terms of stability and robustness. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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17 pages, 7830 KiB  
Article
A Simulation Framework for Developing Autonomous Drone Navigation Systems
by Rafael Casado and Aurelio Bermúdez
Electronics 2021, 10(1), 7; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10010007 - 23 Dec 2020
Cited by 13 | Viewed by 4543
Abstract
Unmanned aerial vehicles are gaining popularity in an ever-increasing range of applications, mainly because they are able to navigate autonomously. In this work, we describe a simulation framework that can help engineering students who are starting out in the field of aerial robotics [...] Read more.
Unmanned aerial vehicles are gaining popularity in an ever-increasing range of applications, mainly because they are able to navigate autonomously. In this work, we describe a simulation framework that can help engineering students who are starting out in the field of aerial robotics to acquire the necessary competences and skills for the development of autonomous drone navigation systems. In our framework, drone behavior is defined in a graphical way, by means of very intuitive state machines, whereas low-level control details have been abstracted. We show how the framework can be used to develop a navigation system proposal according to the rules of the “ESII Drone Challenge” student competition. We also show how the proposal can be evaluated in different test scenarios. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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18 pages, 5214 KiB  
Article
Neural Network-Based Aircraft Conflict Prediction in Final Approach Maneuvers
by Rafael Casado and Aurelio Bermúdez
Electronics 2020, 9(10), 1708; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9101708 - 18 Oct 2020
Cited by 8 | Viewed by 2962
Abstract
Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether [...] Read more.
Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether a particular configuration of aircraft in the final approach phase will break the minimum separation requirements established by aviation rules. To achieve this, the network must be effectively trained with a large enough database, in which configurations are labeled as leading to conflict or not. We detail the way in which this training database has been obtained and the subsequent neural network design and training process. Results show that a simple network can provide a high accuracy, and therefore, we consider that it may be the basis of a useful decision support tool for both air traffic controllers and airborne autonomous navigation systems. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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19 pages, 2247 KiB  
Article
Real-Time Collision-Free Navigation of Multiple UAVs Based on Bounding Boxes
by Paloma Sánchez, Rafael Casado and Aurelio Bermúdez
Electronics 2020, 9(10), 1632; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9101632 - 03 Oct 2020
Cited by 10 | Viewed by 2627
Abstract
Predictably, future urban airspaces will be crowded with autonomous unmanned aerial vehicles (UAVs) offering different services to the population. One of the main challenges in this new scenario is the design of collision-free navigation algorithms to avoid conflicts between flying UAVs. The most [...] Read more.
Predictably, future urban airspaces will be crowded with autonomous unmanned aerial vehicles (UAVs) offering different services to the population. One of the main challenges in this new scenario is the design of collision-free navigation algorithms to avoid conflicts between flying UAVs. The most appropriate collision avoidance strategies for this scenario are non-centralized ones that are dynamically executed (in real time). Existing collision avoidance methods usually entail a high computational cost. In this work, we present Bounding Box Collision Avoidance (BBCA) algorithm, a simplified velocity obstacle-based technique that achieves a balance between efficiency and cost. The performance of the proposal is analyzed in detail in different airspace configurations. Simulation results show that the method is able to avoid all the conflicts in two UAV scenarios and most of them in multi-UAV ones. At the same time, we have found that the penalty of using the BBCA collision avoidance technique on the flying time and the distance covered by the UAVs involved in the conflict is reasonably acceptable. Therefore, we consider that BBCA may be an excellent candidate for the design of collision-free navigation algorithms for UAVs. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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