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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 - 01 Sep 2021

Cited by 14 | Viewed by 6472

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 [...] Read more.

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)

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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 7 | Viewed by 2746

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 [...] Read more.

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)

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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 17 | Viewed by 3031

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 [...] Read more.

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)

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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 15 | Viewed by 4843

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 [...] Read more.

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)

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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 - 01 Jul 2020

Cited by 13 | Viewed by 3032

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 [...] Read more.

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)

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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 6 | Viewed by 3625

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 [...] Read more.

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)

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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 8 | Viewed by 3573

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 [...] Read more.

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)

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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 14 | Viewed by 4950

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 [...] Read more.

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)

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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 24 | Viewed by 4845

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 [...] Read more.

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)

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