Submit to Electronics Review for Electronics Propose a Special Issue

Journal Menu

Journal Browser

Autonomous Navigation Systems for Unmanned Aerial Vehicles

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 48437

Share This Special Issue

Special Issue Editors

Dr. Rodrigo Munguı́a

E-Mail Website
Guest Editor

Department of Computer Science, CUCEI, University of Guadalajara, Blvd. Marcelino Garca Barragn 1421, C.P. 44430 Guadalajara, Jalisco, México
Interests: mobile robotics; unmanned aerial vehicles; navigation systems for autonomous vehicles; automatic control; optimal state estimation and computer vision

Prof. Dr. Antoni Grau

E-Mail Website
Guest Editor

School of Industrial Engineering, Technical University of Catalonia (UPC, BarcelonaTech), E-08028 Barcelona, Spain
Interests: robotic control; system dynamics; industrial robots control and planning; autonomous robots; robot navigation; sensors in robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Autonomous navigation is a fundamental necessity for any application involving unmanned aerial vehicles (UAV). The global positioning system (GPS) and inertial measurements units (IMU), or their fused variant, the inertial navigation systems (INS), represent the most common approaches for addressing the problem of UAVs navigation. Nevertheless, cluttered, and GPS-denied, environments still pose a considerable challenge. Moreover, GPS-based navigation can be unreliable in several scenarios where precision maneuvers are required. This Special Issue is intended to contribute to the research area of autonomous navigation systems for UAVs.

Also, to control and navigate, UAVs require the use of several critical on-board sensors that can generate data enough to perform those tasks. The reading, treatment, processing, and understanding of this data in real time is another open issue that will be covered by this Special Issue. Finally, depending on the UAV usage, specific sensors and actuators will be needed to carry out the operation of the UAV. With these specific sensors and actuators, UAV can be used for many real applications, not only to carry cameras and taking pictures or movies. The proposal and use of new actuators on-board is of great interest in the robotics community. In this Special Issue, papers dealing with these problems will be welcome.

In this Special Issue proposal, potential topics include but are not limited to the following:

Simultaneous localization and mapping;
Visual odometry and visual-based navigation;
GPS-denied methods;
Cooperative navigation;
SCLAM (simultaneous control localization and mapping);
Control and state estimation for UAVs;
Trajectory tracking;
Tracking of dynamic targets;
3D mapping;
Sensory system for flight control;
Sensors and actuators in UAV for applications.

Dr. Rodrigo Munguia
Dr. Antoni Grau
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

Unmanned aerial vehicles
Drone
SLAM
Robot navigation
UAV control
Tracking
Visual odometry
Mapping
Sensors and actuators in UAV

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (9 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

25 pages, 17878 KiB

Open AccessArticle

Multiple Drone Navigation and Formation Using Selective Target Tracking-Based Computer Vision

by Jatin Upadhyay, Abhishek Rawat and Dipankar Deb

Electronics 2021, 10(17), 2125; https://doi.org/10.3390/electronics10172125 - 1 Sep 2021

Cited by 17 | Viewed by 7616

Abstract

Autonomous unmanned aerial vehicles work seamlessly within the GPS signal range, but their performance deteriorates in GPS-denied regions. This paper presents a unique collaborative computer vision-based approach for target tracking as per the image’s specific location of interest. The proposed method tracks any object without considering its properties like shape, color, size, or pattern. It is required to keep the target visible and line of sight during the tracking. The method gives freedom of selection to a user to track any target from the image and form a formation around it. We calculate the parameters like distance and angle from the image center to the object for the individual drones. Among all the drones, the one with a significant GPS signal strength or nearer to the target is chosen as the master drone to calculate the relative angle and distance between an object and other drones considering approximate Geo-location. Compared to actual measurements, the results of tests done on a quadrotor UAV frame achieve

99 %

location accuracy in a robust environment inside the exact GPS longitude and latitude block as GPS-only navigation methods. The individual drones communicate to the ground station through a telemetry link. The master drone calculates the parameters using data collected at ground stations. Various formation flying methods help escort other drones to meet the desired objective with a single high-resolution first-person view (FPV) camera. The proposed method is tested for Airborne Object Target Tracking (AOT) aerial vehicle model and achieves higher tracking accuracy. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

15 pages, 3063 KiB

Open AccessArticle

Toward Autonomous UAV Localization via Aerial Image Registration

by Xuezhi Wang, Allison Kealy, Wenchao Li, Beth Jelfs, Christopher Gilliam, Samantha Le May and Bill Moran

Electronics 2021, 10(4), 435; https://doi.org/10.3390/electronics10040435 - 10 Feb 2021

Cited by 9 | Viewed by 3411

Abstract

Absolute localization of a flying UAV on its own in a global-navigation-satellite-system (GNSS)-denied environment is always a challenge. In this paper, we present a landmark-based approach where a UAV is automatically locked into the landmark scene shown in a georeferenced image via a feedback control loop, which is driven by the output of an aerial image registration. To pursue a real-time application, we design and implement a speeded-up-robust-features (SURF)-based image registration algorithm that focuses efficiency and robustness under a 2D geometric transformation. A linear UAV controller with signals of four degrees of freedom is derived from the estimated transformation matrix. The approach is validated in a virtual simulation environment, with experimental results demonstrating the effectiveness and robustness of the proposed UAV self-localization system. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

26 pages, 5539 KiB

Open AccessArticle

Methodology for Indoor Positioning and Landing of an Unmanned Aerial Vehicle in a Smart Manufacturing Plant for Light Part Delivery

by Pedro Orgeira-Crespo, Carlos Ulloa, Guillermo Rey-Gonzalez and José Antonio Pérez García

Electronics 2020, 9(10), 1680; https://doi.org/10.3390/electronics9101680 - 14 Oct 2020

Cited by 20 | Viewed by 3479

Abstract

Unmanned aerial vehicles (UAV) are spreading their usage in many areas, including last-mile distribution. In this research, a UAV is used for performing light parts delivery to workstation operators within a manufacturing plant, where GPS is no valid solution for indoor positioning. A generic localization solution is designed to provide navigation using RFID received signal strength measures and sonar values. A system on chip computer is onboarded with two missions: first, compute positioning and provide communication with backend software; second, provide an artificial vision system that cooperates with UAV’s navigation to perform landing procedures. An Industrial Internet of Things solution is defined for workstations to allow wireless mesh communication between the logistics vehicle and the backend software. Design is corroborated through experiments that validate planned solutions. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

18 pages, 7245 KiB

Open AccessArticle

An Embedded Platform for Positioning and Obstacle Detection for Small Unmanned Aerial Vehicles

by Salvatore Ponte, Gennaro Ariante, Umberto Papa and Giuseppe Del Core

Electronics 2020, 9(7), 1175; https://doi.org/10.3390/electronics9071175 - 19 Jul 2020

Cited by 18 | Viewed by 5506

Abstract

Unmanned Aerial Vehicles (UAV) with on-board augmentation systems (UAS, Unmanned Aircraft System) have penetrated into civil and general-purpose applications, due to advances in battery technology, control components, avionics and rapidly falling prices. This paper describes the conceptual design and the validation campaigns performed for an embedded precision Positioning, field mapping, Obstacle Detection and Avoiding (PODA) platform, which uses commercial-off-the-shelf sensors, i.e., a 10-Degrees-of-Freedom Inertial Measurement Unit (10-DoF IMU) and a Light Detection and Ranging (LiDAR), managed by an Arduino Mega 2560 microcontroller with Wi-Fi capabilities. The PODA system, designed and tested for a commercial small quadcopter (Parrot Drones SAS Ar.Drone 2.0, Paris, France), estimates position, attitude and distance of the rotorcraft from an obstacle or a landing area, sending data to a PC-based ground station. The main design issues are presented, such as the necessary corrections of the IMU data (i.e., biases and measurement noise), and Kalman filtering techniques for attitude estimation, data fusion and position estimation from accelerometer data. The real-time multiple-sensor optimal state estimation algorithm, developed for the PODA platform and implemented on the Arduino, has been tested in typical aerospace application scenarios, such as General Visual Inspection (GVI), automatic landing and obstacle detection. Experimental results and simulations of various missions show the effectiveness of the approach. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

22 pages, 6469 KiB

Open AccessArticle

A Low-Cost Method of Improving the GNSS/SINS Integrated Navigation System Using Multiple Receivers

by Di Liu, Hengjun Wang, Qingyuan Xia and Changhui Jiang

Electronics 2020, 9(7), 1079; https://doi.org/10.3390/electronics9071079 - 1 Jul 2020

Cited by 14 | Viewed by 3575

Abstract

GNSS (global navigation satellite system) and SINS (strap-down inertial navigation system) integrated navigation systems have been the apparatus for providing reliable and stable position and velocity information (PV). Commonly, there are two solutions to improve the GNSS/SINS integration navigation system accuracy, i.e., employing GNSS with higher position accuracy in the integration system or utilizing the high-grade inertial measurement unit (IMU) to construct the integration system. However, technologies such as RTK (real-time kinematic) and PPP (precise point positioning) that improve GNSS positioning accuracy have higher costs and they cannot work under high dynamic environments. Also, an IMU with high accuracy will lead to a higher cost and larger volume, therefore, a low-cost method to enhance the GNSS/SINS integration accuracy is of great significance. In this paper, multiple receivers based on the GNSS/SINS integrated navigation system are proposed with the aim of providing more precise PV information. Since the chip-scale receivers are cheap, the deployment of multiple receivers in the GNSS/SINS integration will not significantly increase the cost. In addition, two different filtering methods with central and cascaded structure are employed to process the multiple receivers and SINS integration. In the centralized integration filter method, measurements from multiple receivers are directly processed to estimate the SINS errors state vectors. However, the computation load increases heavily due to the rising dimension of the measurement vector. Therefore, a cascaded integration filter structure is also employed to distribute the processing of the multiple receiver and SINS integration. In the cascaded processing method, each receiver is regarded as an individual “sensor”, and a standard federated Kalman filter (FKF) is implemented to obtain an optimal estimation of the navigation solutions. In this paper, a simulation and a field tests are carried out to assess the influence of the number of receivers on the PV accuracy. A detailed analysis of these position and velocity results is presented and the improvements in the PV accuracy demonstrate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

33 pages, 5390 KiB

Open AccessArticle

Cooperative Visual-SLAM System for UAV-Based Target Tracking in GPS-Denied Environments: A Target-Centric Approach

by Juan-Carlos Trujillo, Rodrigo Munguia, Sarquis Urzua and Antoni Grau

Electronics 2020, 9(5), 813; https://doi.org/10.3390/electronics9050813 - 15 May 2020

Cited by 7 | Viewed by 4489

Abstract

Autonomous tracking of dynamic targets by the use of Unmanned Aerial Vehicles (UAVs) is a challenging problem that has practical applications in many scenarios. In this context, a fundamental aspect that must be addressed has to do with the position estimation of aerial robots and a target to control the flight formation. For non-cooperative targets, their position must be estimated using the on-board sensors. Moreover, for estimating the position of UAVs, global position information may not always be available (GPS-denied environments). This work presents a cooperative visual-based SLAM (Simultaneous Localization and Mapping) system that allows a team of aerial robots to autonomously follow a non-cooperative target moving freely in a GPS-denied environment. One of the contributions of this work is to propose and investigate the use of a target-centric SLAM configuration to solve the estimation problem that differs from the well-known World-centric and Robot-centric SLAM configurations. In this sense, the proposed approach is supported by theoretical results obtained from an extensive nonlinear observability analysis. Additionally, a control system is proposed for maintaining a stable UAV flight formation with respect to the target as well. In this case, the stability of control laws is proved using the Lyapunov theory. Employing an extensive set of computer simulations, the proposed system demonstrated potentially to outperform other related approaches. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

23 pages, 2503 KiB

Open AccessArticle

Smooth 3D Path Planning by Means of Multiobjective Optimization for Fixed-Wing UAVs

by Franklin Samaniego, Javier Sanchis, Sergio Garcia-Nieto and Raul Simarro

Electronics 2020, 9(1), 51; https://doi.org/10.3390/electronics9010051 - 28 Dec 2019

Cited by 9 | Viewed by 4119

Abstract

Demand for 3D planning and guidance algorithms is increasing due, in part, to the increase in unmanned vehicle-based applications. Traditionally, two-dimensional (2D) trajectory planning algorithms address the problem by using the approach of maintaining a constant altitude. Addressing the problem of path planning in a three-dimensional (3D) space implies more complex scenarios where maintaining altitude is not a valid approach. The work presented here implements an architecture for the generation of 3D flight paths for fixed-wing unmanned aerial vehicles (UAVs). The aim is to determine the feasible flight path by minimizing the turning effort, starting from a set of control points in 3D space, including the initial and final point. The trajectory generated takes into account the rotation and elevation constraints of the UAV. From the defined control points and the movement constraints of the UAV, a path is generated that combines the union of the control points by means of a set of rectilinear segments and spherical curves. However, this design methodology means that the problem does not have a single solution; in other words, there are infinite solutions for the generation of the final path. For this reason, a multiobjective optimization problem (MOP) is proposed with the aim of independently maximizing each of the turning radii of the path. Finally, to produce a complete results visualization of the MOP and the final 3D trajectory, the architecture was implemented in a simulation with Matlab/Simulink/flightGear. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

22 pages, 1054 KiB

Open AccessArticle

Rollover-Free Path Planning for Off-Road Autonomous Driving

by Xingyu Li, Bo Tang, John Ball, Matthew Doude and Daniel W. Carruth

Electronics 2019, 8(6), 614; https://doi.org/10.3390/electronics8060614 - 31 May 2019

Cited by 17 | Viewed by 5969

Abstract

Perception, planning, and control are three enabling technologies to achieve autonomy in autonomous driving. In particular, planning provides vehicles with a safe and collision-free path towards their destinations, accounting for vehicle dynamics, maneuvering capabilities in the presence of obstacles, traffic rules, and road boundaries. Existing path planning algorithms can be divided into two stages: global planning and local planning. In the global planning stage, global routes and the vehicle states are determined from a digital map and the localization system. In the local planning stage, a local path can be achieved based on a global route and surrounding information obtained from sensors such as cameras and LiDARs. In this paper, we present a new local path planning method, which incorporates a vehicle’s time-to-rollover model for off-road autonomous driving on different road profiles for a given predefined global route. The proposed local path planning algorithm uses a 3D occupancy grid and generates a series of 3D path candidates in the s-p coordinate system. The optimal path is then selected considering the total cost of safety, including obstacle avoidance, vehicle rollover prevention, and comfortability in terms of path smoothness and continuity with road unevenness. The simulation results demonstrate the effectiveness of the proposed path planning method for various types of roads, indicating its wide practical applications to off-road autonomous driving. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Figure 1

12 pages, 3531 KiB

Open AccessArticle

Active-Model-Based Control for the Quadrotor Carrying a Changed Slung Load

by Kui Yi, Xiao Liang, Yuqing He, Liying Yang and Jianda Han

Electronics 2019, 8(4), 461; https://doi.org/10.3390/electronics8040461 - 25 Apr 2019

Cited by 28 | Viewed by 5420

Abstract

In this paper, a simple active-model-based control scheme is developed for the quadrotor slung load (QSL) system. The scheme works to improve the rejection of the influences caused by the abruptly changed load as a complementary enhancement while maintaining the structure and parameters of the original controller. A linearized model is first constructed with respect to the hovering state of a quadrotor. Modeling error is then introduced to describe the uncertainties caused by the load change and the simplified model. The modeling error is actively estimated by a Kalman filter (KF), while the estimation is further integrated into a normal controller, to enhance its performance of disturbance rejection. Experiments are conducted on a quadrotor controlled by the Pixhawk, which is one of the most popular controllers commercially available on the market. The improvements of the proposed scheme are shown by the comparisons between the controls with and without the active-model-based enhancement. The experiments also indicate that, with its simple structure and less computational algorithm, this active-model-based enhancement would be a feasible approach to enhance the commercial UAV controller to handle more uncertainties. Full article

(This article belongs to the Special Issue Autonomous Navigation Systems for Unmanned Aerial Vehicles)

► Show Figures

Journal Menu

Journal Browser

Autonomous Navigation Systems for Unmanned Aerial Vehicles

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (9 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI