scholarly journals Onboard Visual Horizon Detection for Unmanned Aerial Systems with Programmable Logic

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 614 ◽  
Author(s):  
Antal Hiba ◽  
Levente Márk Sántha ◽  
Tamás Zsedrovits ◽  
Levente Hajder ◽  
Akos Zarandy
Keyword(s):  
Vision System ◽  
Computational Cost ◽  
Detection Algorithm ◽  
Initial Guess ◽  
Unmanned Aircraft ◽  
Unmanned Aerial Systems ◽  
Single Shot ◽  
Camera Model ◽  
Radial Distortion ◽  
Horizon Detection

We introduce and analyze a fast horizon detection algorithm with native radial distortion handling and its implementation on a low power field programmable gate array (FPGA) development board in this paper. The algorithm is suited for visual applications in an airborne environment, that is on board a small unmanned aircraft. The algorithm was designed to have low complexity because of the power consumption requirements. To keep the computational cost low, an initial guess for the horizon is used, which is provided by the attitude heading reference system of the aircraft. The camera model takes radial distortions into account, which is necessary for a wide-angle lens used in most applications. This paper presents formulae for distorted horizon lines and a gradient sampling-based resolution-independent single shot algorithm for finding a horizon with radial distortion without undistortion of the complete image. The implemented algorithm is part of our visual sense-and-avoid system, where it is used for the sky-ground separation, and the performance of the algorithm is tested on real flight data. The FPGA implementation of the horizon detection method makes it possible to add this efficient module to any FPGA-based vision system.

scholarly journals Estimation of Wind Turbine Angular Velocity Remotely Found on Video Mining and Convolutional Neural Network

2020 ◽  
Vol 10 (10) ◽  
pp. 3544 ◽  
Author(s):  
Mahdi Bahaghighat ◽  
Qin Xin ◽  
Seyed Ahmad Motamedi ◽  
Morteza Mohammadi Zanjireh ◽  
Antoine Vacavant
Keyword(s):  
Deep Learning ◽  
Angular Velocity ◽  
Wind Turbine ◽  
Intelligent Systems ◽  
Wind Farm ◽  
Vision System ◽  
Detection Algorithm ◽  
Single Shot ◽  
Video Mining ◽  
Other Information

Today, energy issues are more important than ever. Because of the importance of environmental concerns, clean and renewable energies such as wind power have been most welcomed globally, especially in developing countries. Worldwide development of these technologies leads to the use of intelligent systems for monitoring and maintenance purposes. Besides, deep learning as a new area of machine learning is sharply developing. Its strong performance in computer vision problems has conducted us to provide a high accuracy intelligent machine vision system based on deep learning to estimate the wind turbine angular velocity, remotely. This velocity along with other information such as pitch angle and yaw angle can be used to estimate the wind farm energy production. For this purpose, we have used SSD (Single Shot Multi-Box Detector) object detection algorithm and some specific classification methods based on DenseNet, SqueezeNet, ResNet50, and InceptionV3 models. The results indicate that the proposed system can estimate rotational speed with about 99.05 % accuracy.

Driving Torsion Scans with Wavefront Propagation

2020 ◽  
Author(s):  
Yudong Qiu ◽  
Daniel Smith ◽  
Chaya Stern ◽  
mudong feng ◽  
Lee-Ping Wang
Keyword(s):  
Potential Energy ◽  
Force Field ◽  
Degrees Of Freedom ◽  
Computational Cost ◽  
Initial Guess ◽  
Field Development ◽  
Force Field Development ◽  
Wavefront Propagation ◽  
Open Source Software Package

<div>The parameterization of torsional / dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields.</div><div>Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms.</div><div>To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values.</div><div>However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses.</div><div>In this paper we propose a systematic and versatile workflow called \textit{TorsionDrive} to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development.</div><div>The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described.</div><div>The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.</div>

scholarly journals Concrete Crack Detection Based on Well-Known Feature Extractor Model and the YOLO_v2 Network

2021 ◽  
Vol 11 (2) ◽  
pp. 813
Author(s):  
Shuai Teng ◽  
Zongchao Liu ◽  
Gongfa Chen ◽  
Li Cheng
Keyword(s):  
Feature Extraction ◽  
Crack Detection ◽  
Computational Cost ◽  
Concrete Structures ◽  
Detection Algorithm ◽  
Computational Time ◽  
Image Size ◽  
Important Indicator ◽  
Feature Extractor ◽  
Model Training

This paper compares the crack detection performance (in terms of precision and computational cost) of the YOLO_v2 using 11 feature extractors, which provides a base for realizing fast and accurate crack detection on concrete structures. Cracks on concrete structures are an important indicator for assessing their durability and safety, and real-time crack detection is an essential task in structural maintenance. The object detection algorithm, especially the YOLO series network, has significant potential in crack detection, while the feature extractor is the most important component of the YOLO_v2. Hence, this paper employs 11 well-known CNN models as the feature extractor of the YOLO_v2 for crack detection. The results confirm that a different feature extractor model of the YOLO_v2 network leads to a different detection result, among which the AP value is 0.89, 0, and 0 for ‘resnet18’, ‘alexnet’, and ‘vgg16’, respectively meanwhile, the ‘googlenet’ (AP = 0.84) and ‘mobilenetv2’ (AP = 0.87) also demonstrate comparable AP values. In terms of computing speed, the ‘alexnet’ takes the least computational time, the ‘squeezenet’ and ‘resnet18’ are ranked second and third respectively; therefore, the ‘resnet18’ is the best feature extractor model in terms of precision and computational cost. Additionally, through the parametric study (influence on detection results of the training epoch, feature extraction layer, and testing image size), the associated parameters indeed have an impact on the detection results. It is demonstrated that: excellent crack detection results can be achieved by the YOLO_v2 detector, in which an appropriate feature extractor model, training epoch, feature extraction layer, and testing image size play an important role.

Based on the CO2 Gas Shielded Welding Molten Pool Image Edge Detection Algorithm

2013 ◽  
Vol 437 ◽  
pp. 840-844 ◽  
Author(s):  
Xiao Gang Liu ◽  
Bing Zhao
Keyword(s):  
Edge Detection ◽  
Molten Pool ◽  
High Speed ◽  
Vision System ◽  
Detection Algorithm ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Defect Recognition ◽  
Pool Image

This paper use the passive vision system through high-speed camera collects molten pool images; and then according to the frequency domain characteristics of the weld pool image Butterworth low-pass filter; gradient method for image enhancement obtained after pretreatment. Research Roberts, Sobel, Prewitt, Log, Zerocross, and Canny 6 both traditional differential operator edge detection processing results. Through comparison and analysis of choosing threshold for [0.1, 0. Canny operator can get the ideal molten pool edge character, for subsequent welding molten pool defect recognition provides favorable conditions.

scholarly journals Method to Characterize Potential UAS Encounters Using Open Source Data

Aerospace ◽  
2020 ◽  
Vol 7 (11) ◽  
pp. 158
Author(s):  
Andrew Weinert
Keyword(s):  
Open Source ◽  
Unmanned Aircraft ◽  
Unmanned Aerial Systems ◽  
Horizontal Distance ◽  
Geospatial Information ◽  
Open Source Data ◽  
Source Data ◽  
Aircraft Trajectories ◽  
Processing Techniques ◽  
Aerial Systems

As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.

scholarly journals Experimental Comparison of Direct and Active Throttle Control of a 7 kW Turboelectric Power System for Unmanned Aircraft

2021 ◽  
Vol 11 (22) ◽  
pp. 10608
Author(s):  
Johnathan Burgess ◽  
Timothy Runnels ◽  
Joshua Johnsen ◽  
Joshua Drake ◽  
Kurt Rouser
Keyword(s):  
Transient Behavior ◽  
Unmanned Aircraft ◽  
Experimental Comparison ◽  
Small Scale ◽  
Unmanned Aerial Systems ◽  
Operational Parameters ◽  
Turbine Engine ◽  
Control Scheme ◽  
Aerial Systems ◽  
Electric Loads

This article compares direct turbine throttle control and active turbine throttle control for a turboelectric system; the featured turboprop is rated for 7 kW of shaft output power. The powerplant is intended for applications in unmanned aerial systems and requires a control system to produce different amounts of power for varying mission legs. The most straightforward control scheme explored is direct turbine control, which is characterized by the pilot controlling the throttle of the turbine engine. In contrast, active control is characterized by the turbine reacting to the power demanded by the electric motors or battery recharge cycle. The transient response to electric loads of a small-scale turboelectric system is essential in identifying and characterizing such a system’s safe operational parameters. This paper directly compares the turbogenerator’s transient behavior to varying electric loads and categorizes its dynamic response. A proportional, integral, and derivative (PID) control algorithm was utilized as an active throttle controller through a microcontroller with battery power augmentation for the turboelectric system. This controller manages the turbine’s throttle reactions in response to any electric load when applied or altered. By comparing the system’s response with and without the controller, the authors provide a method to safely minimize the response time of the active throttle controller for use in the real-world environment of unmanned aircraft.

UAS Mission Path Planning System (MPPS) Using Hybrid-Game Coupled to Multi-Objective Optimiser

2009 ◽  
Author(s):  
DongSeop Lee ◽  
Jacques Periaux ◽  
Luis Felipe Gonzalez
Keyword(s):  
Path Planning ◽  
Computational Cost ◽  
Optimization Techniques ◽  
Planning System ◽  
Unmanned Aerial Systems ◽  
Three Dimension ◽  
Design Quality ◽  
Nsga Ii ◽  
Start Position ◽  
Multi Objective

This paper presents the application of advanced optimization techniques to Unmanned Aerial Systems (UAS) Mission Path Planning System (MPPS) using Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and a Hybrid Game strategy are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The resulting trajectories on a three-dimension terrain are collision-free and are represented by using Be´zier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a Hybrid-Game strategy to a MOEA and for a MPPS.

Development and Flight Validation of Proposed Unmanned Aerial System Handling Qualities Requirements

2021 ◽  
Author(s):  
Christina M. Ivler ◽  
Kevin Truong ◽  
Declan Kerwin ◽  
Joel Otomize ◽  
Danielle Parmer ◽  
...  
Keyword(s):  
Large Scale ◽  
Performance Standards ◽  
Unmanned Aircraft ◽  
Performance Standard ◽  
Great Promise ◽  
Unmanned Aerial Systems ◽  
Dynamic Scaling ◽  
Scoring Method ◽  
Handling Qualities ◽  
Aerial Systems

Unmanned aerial systems, commonly known as drones, present new opportunities to perform autonomous tasks. Handling qualities requirements for manned vertical lift aircraft have been well defined and documented. The need to define handling qualities requirements for vertical take-off and landing (VTOL) unmanned aerial systems (UAS) to meet mission demands is of paramount importance for all potential operators and procurement agencies. One way to relate handling qualities specifications of large-scale manned and subscale unmanned aircraft is through Froude dynamic scaling. Froude dynamic scaling based on hub-to-hub distance has shown great promise in relating the natural frequencies of scaled multicopters. There have been recent efforts to develop a VTOL-UAS handling qualities standard by scaling mission task elements and rating their performance through a Trajectory, Tracking, and Aggression (TTA) score. This paper proposes a new performance standard adapted from the TTA scoring method, along with a modified Cooper–Harper scale as a VTOL-UAS handling qualities framework that is consistent with the spirit of Aeronautical Design Standard 33 (ADS-33). These newly proposed performance standards were then validated through simulation and flight testing on a small hexacopter UAS, flown at the University of Portland. A key outcome of this work is the flight verification of a key dynamic response metric, the disturbance rejection bandwidth, and associated validation of Froude scaling for predicted handling qualities metrics.

scholarly journals Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 521 ◽  
Author(s):  
Gloria Salmoral ◽  
Monica Rivas Casado ◽  
Manoranjan Muthusamy ◽  
David Butler ◽  
Prathyush Menon ◽  
...  
Keyword(s):  
Risk Management ◽  
Emergency Response ◽  
Flood Risk ◽  
Online Survey ◽  
Practical Experience ◽  
Flood Risk Management ◽  
Unmanned Aircraft ◽  
Unmanned Aerial Systems ◽  
Effective Response ◽  
Deployment Analysis

There is increasing interest in using Unmanned Aircraft Systems (UAS) in flood risk management activities including in response to flood events. However, there is little evidence that they are used in a structured and strategic manner to best effect. An effective response to flooding is essential if lives are to be saved and suffering alleviated. This study evaluates how UAS can be used in the preparation for and response to flood emergencies and develops guidelines for their deployment before, during and after a flood event. A comprehensive literature review and interviews, with people with practical experience of flood risk management, compared the current organizational and operational structures for flood emergency response in both England and India, and developed a deployment analysis matrix of existing UAS applications. An online survey was carried out in England to assess how the technology could be further developed to meet flood emergency response needs. The deployment analysis matrix has the potential to be translated into an Indian context and other countries. Those organizations responsible for overseeing flood risk management activities including the response to flooding events will have to keep abreast of the rapid technological advances in UAS if they are to be used to best effect.

scholarly journals Object Detection Algorithm Based on Multiheaded Attention

2019 ◽  
Vol 9 (9) ◽  
pp. 1829 ◽  
Author(s):  
Jie Jiang ◽  
Hui Xu ◽  
Shichang Zhang ◽  
Yujie Fang
Keyword(s):  
Object Detection ◽  
Linear Interpolation ◽  
Detection Algorithm ◽  
Attention Mechanism ◽  
Visual Object ◽  
Single Shot ◽  
Object Class ◽  
Feature Information ◽  
Base Network ◽  
Detector Model

This study proposes a multiheaded object detection algorithm referred to as MANet. The main purpose of the study is to integrate feature layers of different scales based on the attention mechanism and to enhance contextual connections. To achieve this, we first replaced the feed-forward base network of the single-shot detector with the ResNet–101 (inspired by the Deconvolutional Single-Shot Detector) and then applied linear interpolation and the attention mechanism. The information of the feature layers at different scales was fused to improve the accuracy of target detection. The primary contributions of this study are the propositions of (a) a fusion attention mechanism, and (b) a multiheaded attention fusion method. Our final MANet detector model effectively unifies the feature information among the feature layers at different scales, thus enabling it to detect objects with different sizes and with higher precision. We used the 512 × 512 input MANet (the backbone is ResNet–101) to obtain a mean accuracy of 82.7% based on the PASCAL visual object class 2007 test. These results demonstrated that our proposed method yielded better accuracy than those provided by the conventional Single-shot detector (SSD) and other advanced detectors.

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