Implementation of vision-based automatic guidance system on a fixed-wing unmanned aerial vehicle

2012 ◽  
Vol 116 (1183) ◽  
pp. 895-914 ◽  
Author(s):  
C-S Lee ◽  
F-B Hsiao
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Image Plane ◽  
Guidance System ◽  
Aerial Images ◽  
Colour Properties ◽  
Image Processing Algorithm ◽  
Automatic Guidance ◽  
Aerial Vehicle

Abstract This paper presents the design and implementation of a vision-based automatic guidance system on a fixed-wing unmanned aerial vehicle (UAV). The system utilises a low-cost ordinary video camera and simple but efficient image processing techniques widely used in computer-vision technology. The paper focuses on the identification and extraction of geographical tracks such as rivers, coastlines, and roads from real-time aerial images. The image processing algorithm primarily uses colour properties to isolate the geographical track of interest from its background. Hough transform is eventually used to curve-fit the profile of the track which yields a reference line on the image plane. A guidance algorithm is then derived based on this information. In order to test the vision-based automatic guidance system in the laboratory without actually flying the UAV, a hardware-in-the-loop simulation system is developed. Description regarding the system and significant simulation result are presented in the paper. Finally, an actual test flight where the UAV successfully follows a stretch of a river under automatic vision-based guidance is also presented and discussed.

scholarly journals Design and construction of a prototype of an unmanned aerial vehicle equipped with artificial vision for the search of people

2017 ◽  
Vol 15 (41) ◽  
pp. 9-26
Author(s):  
Andrés Espinal Rojas ◽  
Andrés Arango Espinal ◽  
Luis Ramos ◽  
Jorge Humberto Erazo Aux
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Wireless Transmission ◽  
Image Processing Algorithm ◽  
Image Capture ◽  
Aerial View ◽  
Aerial Vehicle ◽  
Recognition Of Objects ◽  
Technological Challenge

This paper describes the development and implementation of a six-pointed Unmanned Aerial Vehicle [UAV] prototype, designed for finding lost people in hard to access areas, using Arduino MultiWii platform. A platform capable of performing a stable flight to identify people through an on-board camera and an image processing algorithm was developed. Although the use of UAV represents a low cost and quick response –in terms of displacement– solution, capable to prevent or reduce the number of deaths of lost people in away places, also represents a technological challenge, since the recognition of objects from an aerial view is difficult, due to the distance of the UAV to the objective, the UAV’s position and its constant movement. The solution proposed implements an aerial device that performs the image capture, wireless transmission and image processing while it is in a controlled and stable flight.

scholarly journals Rain Gutter Detection in Aerial Images for Aedes aegypti Mosquito Prevention

2020 ◽  
Author(s):  
Lucas Rossi ◽  
André Backes ◽  
Jefferson Souza
Keyword(s):  
Image Processing ◽  
Aedes Aegypti ◽  
Unmanned Aerial Vehicle ◽  
Digital Image Processing ◽  
Yellow Fever ◽  
Automatic System ◽  
Aerial Images ◽  
Aerial Vehicle ◽  
Mosquito Breeding ◽  
Breeding Location

The detection of Aedes aegypti mosquito is essential in the prevention process of serious diseases such as dengue, yellow fever, chikungunya, and Zika virus. Common approaches consist of surveillance agents who need to enter residences to find and eliminate these outbreaks, but often they are unable to do this work due to the absence or resistance of the resident. This paper proposes an automatic system that uses aerial images obtained through a camera coupled from an Unmanned Aerial Vehicle (UAV) to identify rain gutters from a shed that may be mosquitoes’ foci. We use Digital Image Processing (DIP) techniques to differentiate the objects that may or may not be those foci of the mosquito-breeding. The experimental results show that the system is capable of automatically detecting the appropriately mosquito-breeding location.

scholarly journals Photogrammetric mapping using unmanned aerial vehicle

2014 ◽  
Vol XL-1 ◽  
pp. 129-133 ◽  
Author(s):  
N. Graça ◽  
E. Mitishita ◽  
J. Gonçalves
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Rural Areas ◽  
Low Cost ◽  
Direct Determination ◽  
Aerial Images ◽  
Image Block ◽  
Exterior Orientation ◽  
Aerial Vehicle ◽  
Urban And Rural Areas ◽  
Orientation Parameters

Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

scholarly journals Autonomous, Onboard Vision-Based Trash and Litter Detection in Low Altitude Aerial Images Collected by an Unmanned Aerial Vehicle

2021 ◽  
Vol 13 (5) ◽  
pp. 965
Author(s):  
Marek Kraft ◽  
Mateusz Piechocki ◽  
Bartosz Ptak ◽  
Krzysztof Walas
Keyword(s):  
Neural Networks ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Detection Algorithm ◽  
Aerial Images ◽  
Detection Accuracy ◽  
Deep Convolutional Neural Networks ◽  
Domain Specific ◽  
Aerial Vehicle ◽  
Low Altitude

Public littering and discarded trash are, despite the effort being put to limit it, still a serious ecological, aesthetic, and social problem. The problematic waste is usually localised and picked up by designated personnel, which is a tiresome, time-consuming task. This paper proposes a low-cost solution enabling the localisation of trash and litter objects in low altitude imagery collected by an unmanned aerial vehicle (UAV) during an autonomous patrol mission. The objects of interest are detected in the acquired images and put on the global map using a set of onboard sensors commonly found in typical UAV autopilots. The core object detection algorithm is based on deep, convolutional neural networks. Since the task is domain-specific, a dedicated dataset of images containing objects of interest was collected and annotated. The dataset is made publicly available, and its description is contained in the paper. The dataset was used to test a range of embedded devices enabling the deployment of deep neural networks for inference onboard the UAV. The results of measurements in terms of detection accuracy and processing speed are enclosed, and recommendations for the neural network model and hardware platform are given based on the obtained values. The complete system can be put together using inexpensive, off-the-shelf components, and perform autonomous localisation of discarded trash, relieving human personnel of this burdensome task, and enabling automated pickup planning.

scholarly journals Utilizing drone technology in the civil engineering

2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Civil Engineering ◽  
Aerial Images ◽  
General Overview ◽  
Aerial Photogrammetry ◽  
Different Types ◽  
Aerial Vehicle

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.

Marker-guided auto-landing on a moving platform

2017 ◽  
Vol 5 (1) ◽  
pp. 28-42 ◽  
Author(s):  
Iryna Borshchova ◽  
Siu O’Young
Keyword(s):  
Image Processing ◽  
Visual Servoing ◽  
Low Cost ◽  
Field Tests ◽  
Processing Algorithm ◽  
Prototype System ◽  
Image Processing Algorithm ◽  
Suggested Approach ◽  
Content Type ◽  
Moving Platform

Purpose The purpose of this paper is to develop a method for a vision-based automatic landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving platform. The landing system must be highly accurate and meet the size, weigh, and power restrictions of a small UAV. Design/methodology/approach The vision-based landing system consists of a pattern of red markers placed on a moving target, an image processing algorithm for pattern detection, and a servo-control for tracking. The suggested approach uses a color-based object detection and image-based visual servoing. Findings The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100×100 mm), light-weight (100 g), and consumes little power (under 2 W). Originality/value The novelty and the main contribution of the suggested approach are a creative combination of work in two fields: image processing and controls as applied to the UAV landing. The developed image processing algorithm has low complexity as compared to other known methods, which allows its implementation on general-purpose low-cost hardware. The theoretical design has been verified systematically via simulations and then outdoors field tests.

scholarly journals Suitability of a Non-Dispersive Infrared Methane Sensor Package for Flux Quantification Using an Unmanned Aerial Vehicle

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4705 ◽  
Author(s):  
Adil Shah ◽  
Joseph Pitt ◽  
Khristopher Kabbabe ◽  
Grant Allen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Mole Fraction ◽  
Low Cost ◽  
Methane Flux ◽  
Gain Factor ◽  
Measured Signal ◽  
Allan Deviation ◽  
Methane Sensor ◽  
Aerial Vehicle ◽  
Flux Quantification

Point-source methane emission flux quantification is required to help constrain the global methane budget. Facility-scale fluxes can be derived using in situ methane mole fraction sampling, near-to-source, which may be acquired from an unmanned aerial vehicle (UAV) platform. We test a new non-dispersive infrared methane sensor by mounting it onto a small UAV, which flew downwind of a controlled methane release. Nine UAV flight surveys were conducted on a downwind vertical sampling plane, perpendicular to mean wind direction. The sensor was first packaged in an enclosure prior to sampling which contained a pump and a recording computer, with a total mass of 1.0 kg. The packaged sensor was then characterised to derive a gain factor of 0.92 ± 0.07, independent of water mole fraction, and an Allan deviation precision (at 1 Hz) of ±1.16 ppm. This poor instrumental precision and possible short-term drifts made it non-trivial to define a background mole fraction during UAV surveys, which may be important where any measured signal is small compared to sources of instrumental uncertainty and drift. This rendered the sensor incapable of deriving a meaningful flux from UAV sampling for emissions of the order of 1 g s−1. Nevertheless, the sensor may indeed be useful when sampling mole fraction enhancements of the order of at least 10 ppm (an order of magnitude above the 1 Hz Allan deviation), either from stationary ground-based sampling (in baseline studies) or from mobile sampling downwind of sources with greater source flux than those observed in this study. While many methods utilising low-cost sensors to determine methane flux are being developed, this study highlights the importance of adequately characterising and testing all new sensors before they are used in scientific research.

scholarly journals Simulation of UAV Systems

10.14311/754 ◽  
2005 ◽  
Vol 45 (4) ◽  
Author(s):  
P. Kaňovský ◽  
L. Smrcek ◽  
C. Goodchild
Keyword(s):  
Dynamical System ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Design Tool ◽  
Inertial System ◽  
Principal Function ◽  
Low Weight ◽  
High Bandwidth ◽  
Aerial Vehicle ◽  
Selection Of

The study described in this paper deals with the issue of a design tool for the autopilot of an Unmanned Aerial Vehicle (UAV) and the selection of the airdata and inertial system sensors. This project was processed in cooperation with VTUL a PVO o.z. [1]. The feature that distinguishes the autopilot requirements of a UAV (Figs. 1, 7, 8) from the flight systems of conventional manned aircraft is the paradox of controlling a high bandwidth dynamical system using sensors that are in harmony with the low cost low weight objectives that UAV designs are often expected to achieve. The principal function of the autopilot is flight stability, which establishes the UAV as a stable airborne platform that can operate at a precisely defined height. The main sensor for providing this height information is a barometric altimeter. The solution to the UAV autopilot design was realised with simulations using the facilities of Matlab® and in particular Simulink®[2]. 

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