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Abstract

Natural or man-made disasters often result in trapped victims under rubble piles. In such emergency response situations, Urban Search and Rescue (USaR) teams have to make quick decisions to determine the location of possible trapped humans. The fast 3D modelling of collapsed buildings using images from Unmanned Aerial Vehicles (UAVs) can significantly help the USaR operations and improve disaster response. The a-priori establishment of a proper workflow for fast and reliable image-based 3D modelling and the careful parameterization in every step of the photogrammetric process are crucial aspects that ensure the readiness in an emergency situation. This paper evaluates powerful commercial and open-source software for the creation of 3D models of disaster scenes using UAV imagery for rapid response situations and conducts a thorough analysis on the parameters of the various modelling steps that may lead to the desired results for USaR operations. The main result of our analysis is the establishment of optimized photogrammetric procedures with the scope of fast 3D modelling of disaster scenes, to assist USaR teams and increase survival rates.

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... They are expected to communicate with many different smart objects, such as sensors and embedded devices [64]. Their mobility [61], the ability to provide real-time data [65] and the potential to carry hardware for on-board decision making [66] make UAVs the ideal candidate. Indeed, as projected by in [63], UAVs are expected to play a critical role in smart cities and city-wide IoT (Internet-of-Things) infrastructure. ...
... As such, they can operate in three spacial dimensions (i.e., get close to objects even if these are at a distance from the ground, assume elevated positions above locations or objects of interest and chose their position on the basis of it being sustainable and not affecting other participants of smart city operations), are not restricted by congested networks on the ground and can autonomously adapt their exact location and the settings of their sensors to deliver the best possible service. Platform mounted sensors can contribute to public safety in the areas of imagery [65,74,75], monitoring [34,40,53,69,74,[76][77][78][79][80][81][82][83][84][85][86][87][88] and surveillance [34,40,46,48,53,78,82,87,[89][90][91]]. ...
... UAVs have been used to support patrolling [70,88] (e.g., border patrol [34,53], coast patrol [95] and even indoor patrol [99]), to inform situational awareness [33,65,81,88,96,97], for costal management [68], in the context of terrain survey and mapping [90] and, generally, for data collection [89]. ...
Article
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The use of UAVs in areas ranging from agriculture over urban services to entertainment or simply as a hobby has rapidly grown over the last years. Regarding serious/commercial applications, UAVs have been considered in the literature, especially as mobile sensing/actuation platforms (i.e., as a delivery platform for an increasingly wide range of sensors and actuators). With regard to timely, cost-effective and very rich data acquisition, both, NEC Research as well as TNO are pursuing investigations into the use of UAVs and swarms of UAVs for scenarios where high-resolution requirements, prohibiting environments or tight time constraints render traditional approaches ineffective. In this review article, we provide a brief overview of safety and security-focused application areas that we identified as main targets for industrial and commercial projects, especially in the context of intelligent autonomous systems and autonomous/semi-autonomously operating swarms. We discuss a number of challenges related to the deployment of UAVs in general and to their deployment within the identified application areas in particular. As such, this article is meant to serve as a review and overview of the literature and the state-of-the-art, but also to offer an outlook over our possible (near-term) future work and the challenges that we will face there.
... A.2 Rescue in areas with difficult access [63][64][65][66]. ...
... As an example, none of the UAS used in the disasters and emergency category (A) provides processing features, although these features are required for the category (see Table 3). These features are replaced, in most cases, by storage capacity so that the images recorded are stored in the device and processed by the server later on, once the UAS has landed (e.g., in [60,64] or [65]). ...
Article
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Sustainability is at the heart of many application fields where the use of Unmanned Aerial Systems (UAS) is becoming more and more important (e.g., agriculture, fire detection and prediction, environmental surveillance, mapping, etc.). However, their usage and evolution are highly conditioned by the specific application field they are designed for, and thus, they cannot be easily reused among different application fields. From this point of view, being that they are not multipurpose, we can say that they are not fully sustainable. Bearing this in mind, the objective of this paper is two-fold: on the one hand, to identify the whole set of features that must be provided by a UAS to be considered sustainable and to show that there is no UAS satisfying all these features; on the other hand, to present an open and sustainable UAS architecture that may be used to build UAS on demand to provide the features needed in each application field. Since this architecture is mainly based on software and hardware adaptability, it contributes to the technical sustainability of cities.
... Second, these airborne machine's mere operation, which relies intensely on their potential cyber pose a great menace to individuals and property. 48 In disaster, UAVs have been widely used for collection of data, 49 missions including search and rescue (SAR), [50][51][52][53][54][55][56][57] triage, 58 surveillance (urban, 59 base station, 38 border 60 ) and monitoring, 53,[61][62][63][64][65] imagery. 51,61,66 This study covers the vast applications of UAVs from military to disaster situations, thereby finding its way in numerous applications of the real world. ...
... 48 In disaster, UAVs have been widely used for collection of data, 49 missions including search and rescue (SAR), [50][51][52][53][54][55][56][57] triage, 58 surveillance (urban, 59 base station, 38 border 60 ) and monitoring, 53,[61][62][63][64][65] imagery. 51,61,66 This study covers the vast applications of UAVs from military to disaster situations, thereby finding its way in numerous applications of the real world. To the best of the author's knowledge, this is the first comprehensive study to use the three powerful techniques [blockchain, machine learning (ML), watermarking] for securing UAVs applications. ...
Article
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Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. The applications include smart things, smart transportation, smart cities, smart healthcare, smart personal care, smart house, smart industries, and so on. Due to the sensitive applications of UAVs, the security has become a major concern, and therefore, efficient techniques are required to protect captured data from hackers and the fictitious activities from illegitimate users. Machine learning (ML) techniques play a vital role in improving UAVs' security intelligently, while blockchain is recent technology for decentralized UAVs and security. Furthermore, watermarking guarantees digital media to be authenticated, protected, and copyright. Therefore, we provide a comprehensive survey of optimal techniques, which are used for securing UAVs applications in terms of blockchain, ML, and watermarking. Furthermore, we introduce each technique with the advantages and suitably used for securing UAVs collaboration applications. This survey contributes to a better understanding of the blockchain, ML, and watermarking techniques for securing UAVs and sheds new light on challenges and opportunities on subject applications.
... For this reason, increasing attention is being paid to alternative airborne remote sensing systems, such as UAVs. Photos taken by UAVs can be used to construct a 3D model of a particular point of interest (POI) using the structure-from-motion (SfM) and multiview stereo (MVS) methods [7][8][9] . ...
Article
Full-text available
Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In particular, building damage should be assessed to account for possible casualties, and displaced populations, to estimate long-term shelter capacities, and to assess the damage to services that depend on essential infrastructure (e.g. hospitals, schools, etc.). Remote sensing techniques, including satellite imagery, can be used to gathering such information so that the overall damage can be assessed. However, specific points of interest among the damaged buildings need higher resolution images and detailed information to assess the damage situation. These areas can be further assessed through unmanned aerial vehicles and 3D model reconstruction. This paper presents a multi-UAV coverage path planning method for the 3D reconstruction of postdisaster damaged buildings. The methodology has been implemented in NetLogo3D, a multi-agent model environment, and tested in a virtual built environment in Unity3D. The proposed method generates camera location points surrounding targeted damaged buildings. These camera location points are filtered to avoid collision and then sorted using the K-means or the Fuzzy C-means methods. After clustering camera location points and allocating these to each UAV unit, a route optimization process is conducted as a multiple traveling salesman problem. Final corrections are made to paths to avoid obstacles and give a resulting path for each UAV that balances the flight distance and time. The paper presents the details of the model and methodologies, and an examination of the texture resolution obtained from the proposed method and the conventional overhead flight with the nadir-looking method used in 3D mappings. The algorithm outperforms the conventional method in terms of the quality of the generated 3D model.
... Recently, drones have been proposed as a tool to support several aspects of disaster response [7,8] such as gathering information on the ground state, 3D mapping [9], situational awareness, logistics planning, damage assessment, communications relay points, and direct SAR missions. They have also been used to support SAR missions [10] through delivery of live-saving equipment such as life vests [11,12], or allowing for audible communication through speakers with people once they are located. ...
Article
Full-text available
Search and rescue (SAR) is a vital line of defense against unnecessary loss of life. However, in a potentially hazardous environment, it is important to balance the risks associated with SAR action. Drones have the potential to help with the efficiency, success rate and safety of SAR operations as they can cover large or hard to access areas quickly. The addition of thermal cameras to the drones provides the potential for automated and reliable detection of people in need of rescue. We performed a pilot study with a thermal-equipped drone for SAR applications in Morecambe Bay. In a variety of realistic SAR scenarios, we found that we could detect humans who would be in need of rescue, both by the naked eye and by a simple automated method. We explore the current advantages and limitations of thermal drone systems, and outline the future path to a useful system for deployment in real-life SAR.
... Use of UAV-borne photogrammetry in emergency has long been the object of several researches [15][16][17][18][19]. ...
Conference Paper
Fire Departments feature specialized teams for Urban Search And Rescue (USAR) activities, operating in case of disasters and in collapse contexts, where the actual situation no longer coincides with any previous survey. In this context, current UAV-borne photogrammetry may offer very effective methods, enabling achievement of to-date knowledge of the status quo. Their effectiveness in these contexts is due to the ability of drones to operate in triple-D areas (Dull, Dusty, Dangerous) and to the remote sensing features inherent in photogrammetry.
... Mainly, the fact that oblique aerial images depict not only horizontal structures (e.g., roofs) but also vertical ones (e.g., building façades) [50], is very fundamental for 3D modelling, as the need for additional terrestrial images may be eliminated thanks to the use of multi-perspective oblique aerial imagery. In this way, less time is required for image acquisition, which constitutes a major advantage for emergency response situations, where the time parameter is very crucial [53]. What is more, image acquisition during an emergency situation is performed under stress and may result either in large unordered datasets or in incomplete datasets. ...
Article
Full-text available
Natural and man-made disasters that may take place due to a catastrophic incident (e.g., earthquake, explosion, terrorist attack) often result in trapped humans under rubble piles. In such emergency response situations, Urban Search and Rescue (USaR) teams have to make quick decisions under stress in order to determine the location of possible trapped victims. Fast 3D modelling of fully or partially collapsed buildings using images from Unmanned Aerial Vehicles (UAVs) can considerably help USaR efforts, thus improving disaster response and increasing survival rates. The a-priori establishment of a proper workflow for fast and reliable image-based 3D modelling and the a priori determination of the parameters that have to be set in each step of the photogrammetric pipeline are critical aspects that ensure the readiness in an emergency response situation. This paper evaluates powerful commercial and open-source software solutions for the 3D reconstruction of disaster scenes for rapid response situations. The software packages are tested using UAV datasets of a real earthquake scene. A thorough analysis on the parameters of the various modelling steps that may lead to desired results for USaR tasks is made and indicative processing chains are proposed, taking into account the restriction of time. Furthermore, some weaknesses of the data acquisition process that have been detected by performing the experiments are outlined and some improvements and additions are proposed, including an initial preprocessing of the images using a graph-based approach.
... Some indicative use cases are the following: (i) applications for which a small number of coplanar GCPs (e.g., lying on the roof of a building) that are distributed in a small area compared with the area of the total image dataset is available; (ii) applications for which the measurement of GCPs in the area of interest is not possible; and (iii) applications for which the person in charge of the orientation process is a non-photogrammetrist. For instance, one application scenario for which the advantages of the proposed algorithm are particularly significant is the orientation of a block of images taken be an unmanned aerial vehicle (UAV) in the case of an emergency scenario for 2D mapping (e.g., Boccardo et al., 2015) or 3D modelling (e.g., Ferworn et al., 2011;Verykokou et al., 2016aVerykokou et al., , 2016bVerykokou et al., 2018) of a disaster area. In such emergency response situations (e.g., earthquake, explosion), the measurement of GCPs is usually not possible in the area of the disaster (e.g., debris of a building). ...
Article
Full-text available
The purpose of this paper is the presentation of a novel algorithm for automatic estimation of the exterior orientation parameters of image datasets, which can be applied in the case that the scene depicted in the images has a planar surface (e.g., roof of a building). The algorithm requires the measurement of four coplanar ground control points (GCPs) in only one image. It uses a template matching method combined with a homography-based technique for transfer of the GCPs in another image, along with an incremental photogrammetry-based Structure from Motion (SfM) workflow, coupled with robust iterative bundle adjustment methods that reject any remaining outliers, which have passed through the checks and geometric constraints imposed during the image matching procedure. Its main steps consist of (i) determination of overlapping images without the need for GPS/INS data; (ii) image matching and feature tracking; (iii) estimation of the exterior orientation parameters of a starting image pair; and (iv) photogrammetry-based SfM combined with iterative bundle adjustment methods. A developed software solution implementing the proposed algorithm was tested using a set of UAV oblique images. Several tests were performed for the assessment of the errors and comparisons with well-established commercial software were made, in terms of automation and correctness of the computed exterior orientation parameters. The results show that the estimated orientation parameters via the proposed solution have comparable accuracy with those ones computed through the commercial software using the highest possible accuracy settings; in addition, double manual work was required by the commercial software compared to the proposed solution.
... Using depth sensors to construct 3D models of the disaster scenes is common in many works; such as [31,32], which provides accurate distances information of the detected objects. In [33], a rescue assistance tool is presented, where a system based on the 3D modeling of the rubble piles is implemented in order to perform photometric analysis of 3D modeling of the disaster scenes and increase the ability to detect possible victims. With the aim of improving the 3D mapping result, a heterogeneous robot collaboration of UGV-UAV is presented in [34]. ...
Article
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The automation of the Wilderness Search and Rescue (WiSAR) task aims for high levels of understanding of various scenery. In addition, working in unfriendly and complex environments may cause a time delay in the operation and consequently put human lives at stake. In order to address this problem, Unmanned Aerial Vehicles (UAVs), which provide potential support to the conventional methods, are used. These vehicles are provided with reliable human detection and tracking algorithms; in order to be able to find and track the bodies of the victims in complex environments, and a robust control system to maintain safe distances from the detected bodies. In this paper, a human detection based on the color and depth data captured from onboard sensors is proposed. Moreover, the proposal of computing data association from the skeleton pose and a visual appearance measurement allows the tracking of multiple people with invariance to the scale, translation and rotation of the point of view with respect to the target objects. The system has been validated with real and simulation experiments, and the obtained results show the ability to track multiple individuals even after long-term disappearances. Furthermore, the simulations present the robustness of the implemented reactive control system as a promising tool for assisting the pilot to perform approaching maneuvers in a safe and smooth manner.
... Medium-quality photogrammetric processing refers to resolution downscaling of one sixteenth of the input resolution (e.g. Verykokou et al., 2016), and it took between 1 h and 14 h to complete the construction of the virtual outcrops analyzed here ( Table 1). The high-quality setting refers to resolution downscaling of a quarter of the original input (e.g. ...
Article
Although virtual outcrops or digital outcrop model applications in geological studies are becoming increasingly common, virtually no attention has been given to acquisition of palaeocurrent data from cross‐strata. Palaeocurrent indicators are abundant in the sedimentary record, mainly as cross‐strata, and present compelling implications for basin analysis, plate tectonics and palaeoenvironmental reconstructions, as well as for sediment transport systems. Palaeocurrents from cross‐strata also comprise a quantifiable parameter in sedimentary successions that can be used in quantitative modelling of depositional architecture with implications for reservoir characterization through outcrop analogue studies. A common obstacle in obtaining large cross‐strata orientation datasets is the limited access to steep and high outcrop faces, as well as financial and time restrictions on field work. To overcome these issues, the simplest workflow for drone‐based acquisition, photogrammetric processing and analysis of virtual outcrops aiming at the attainment of palaeocurrent data from cross‐strata is appraised here. The results show that orientations of cross‐beds measured on virtual outcrops, with and without ground control points, and using two different levels of resolution downsampling, are comparable to field measurements using analogue and electronic devices. Time and financial resources can thus be saved by using the straightforward method presented here to supplement palaeocurrent mapping across wide areas and distinct stratigraphic intervals.
... Photogrammetric approaches are therefore mostly applied to large scale scenarios, e.g. earthquakes [4]. In the TRADR (Long-Term Human-Robot Teaming for Disaster Response) project 3D point clouds are generated from camera images and combined with 3D point clouds from laser scanners carried by ground robots [5]. ...
... To address these two problems, the exploitation of the UAVs' processing of captured images and their knowledge of the covered area. The work in [7] provides a 3D modeling system based on UAVs to help rescue teams to detect the victims. However, this system can be easily affected by the weather or other factors distorting the captured images. ...
Article
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The response time to emergency situations in urban areas is considered as a crucial key in limiting material damage or even saving human lives. Thanks to their "bird's eye view" and their flexible mobility, Unmanned Aerial Vehicles (UAVs) can be a promising candidate for several vital applications. Under these perspectives, we investigate the use of communicating UAVs to detect any incident on the road, provide rescue teams with their exact locations, and plot the fastest path to intervene, while considering the constraints of the roads. To efficiently inform the rescue services, a robust routing scheme is introduced to ensure a high level of communication stability based on an efficient backbone, while considering both the high mobility and the restricted energy capacity of UAVs. This allows both predicting any routing path breakage prior to its occurrence, and carrying out a balanced energy consumption among UAVs. To ensure a rapid intervention by rescue teams, UAVs communicate in an ad hoc fashion with existing vehicles on the ground to estimate the fluidity of the roads. Our system is implemented and evaluated through a series of experiments. The reported results show that each part of the system reliably succeeds in achieving its planned objective.
... In Urban Search and Rescue (USaR) operations have limited time to rescue the trapped victims. For this kind of rapid response situations, the creation of 3D models of disaster scenes using Drone imagery can assist USaR team and increase survival rates [3]. In [4], they use augmented reality system with robot rescuer for Urban Search and Rescue operations. ...
Conference Paper
Natural disasters are increasing day by day as the climate crisis becomes more serious. In a disastrous situation, search and rescue missions are very risky, time-consuming, and resource constraints. A hybrid drone-assisted mixed reality-based system (termed as "MR-Drone") is proposed for conducting search and rescue operations very quickly and efficiently in a disastrous situation like an earthquake, floods, fire breakout, etc. In our proposed system, we use drone’s real-time steaming for generating a 3D map of the target area and this map can be shown in mixed reality device like HoloLens for monitoring the rescue mission. Multiple users can monitor the emergency together in a mixed reality environment using MR-Drone thus reduce the rescue time.
... Via comparison to the achievements of similar technologies in other domains, the hypothesis formulated for this research assumes that three-dimensional and orthophoto mapping will improve aerial assessments of flood-related needs and damages [37,39,40]. The hypothesis is substantiated by the fact that a three-dimensional model enables the user to see a building's elevations from different angles, which is not possible from a two-dimensional perspective. ...
Article
Full-text available
The aim of this research is to provide disaster managers with the results of testing three-dimensional modeling and orthophoto mapping, so as to add value to aerial assessments of flood-related needs and damages. The relevant testing of solutions concerning the real needs of disaster managers is an essential part of the pre-disaster phase. As such, providing evidence-based results of the solutions’ performance is critical with regard to purchasing them and their successful implementation for disaster management purposes. Since disaster response is mostly realized in complex and dynamic, rather than repetitive, environments, it requires pertinent testing methods. A quasi-experimental approach, applied in a form of a full-scale trial meets disaster manager’s requirements as well as addressing limitations resulting from the disaster environment’s characteristics. Three-dimensional modeling and orthophoto mapping have already proven their potential in many professional fields; however, they have not yet been broadly tested for disaster response purposes. Therefore, the objective here is to verify the technologies regarding their applicability in aerial reconnaissance in sudden-onset disasters. The hypothesis assumes that they will improve the efficiency (e.g., time) and effectiveness (e.g., accuracy of revealed data) of this process. The research verifies that the technologies have a potential to facilitate disaster managers with more precise damage assessment; however, their effectivity was less than expected in terms of needs reconnaissance. Secondly, the overall assessment process is heavily burdened by data processing time, however, the technologies allow a reduction of analytical work.
... Significant progress has been made in the estimation of damage sustained from a disaster using satellite remote sensing 7,19 ; however, the details of damage to buildings typically remain unclear because of the scarcity of information about the condition of building walls. For this reason, increasing attention is being paid to structure-from-motion (SfM) and multiview stereo (MVS) photographic surveys conducted using UAVs 11,21,22 . ...
Preprint
Full-text available
For effective disaster relief decision-making, responders require extensive and rapid information on the damage situation in affected areas. Areas with unknown conditions pose a high risk of injury, and working on the ground limits the coverage and speed of information acquisition. An alternative is to exploit aerial observations and, in particular, unmanned aerial vehicles (UAVs). UAVs can be rapidly deployed to access remote areas without risking survey teams. Moreover, large-scale disasters impact wide areas, and multiple UAVs are needed to increase coverage without compromising resolution or speed. Of particular importance for evaluation are assets such as hospitals, shelters and essential infrastructures. UAVs can survey such structures to construct three-dimensional (3D) models for inspection.A structure-from-motion (SfM) survey generates 3D models from multiple images. However, most path planning algorithms for SfM focus on points of interest taken from an individual UAV and consider a single structure. Here, we propose a path design method for multi-UAV SfM surveys. By designing flight paths with sufficient overlap and sidelap ratios for all faces of the surveyed objects, more precise 3D models can be constructed than with conventional methods. The fuzzy C-means method is adopted to reduce the UAV flight loads to a uniform minimum to ensure full battery utilization.
... ορθοεικόνες ή αληθείς ορθοεικόνες) ή την περαιτέρω αξιοποίησή τους σε άλλες εφαρμογές όπως ταξινόμησης, εντοπισμού μεταβολών κ.ά. Στην πράξη οι διαδικασίες DIM έχουν εφαρμοστεί με επιτυχία σε πολλές εφαρμογές, όπως γεωμετρική τεκμηρίωση μνημείων [120][121][122][123][124], αποτύπωση και 3Δ ανακατασκευή κρίσιμων υποδομών [125], αντιμετώπιση καταστάσεων έκτακτης ανάγκης [126][127], 3Δ ανακατασκευή πόλεων [128][129][130][131] κ.ά. Τα τελευταία χρόνια η τεχνική DIM συνδυάζεται με τη μέθοδο υπολογισμού δομής από κίνηση (Structure from Motion-SfM) για την αυτοβαθμονόμηση της χρησιμοποιούμενης μηχανής και τον αυτόματο υπολογισμό των εξωτερικών προσανατολισμών των εικόνων [132][133][134]. ...
... 40 A quantitative comparative study regarding reconstruction accuracy and computational cost among these commercial, free, and/or open-source software tools is shown in one of our recent works. 41 The results show that the minimum computational time required for the acquisition of a coarse 3-D model is lower in PhotoScan (commercial software), but the generated model has significantly lower density than the one created by the other toolkits due to the smoothing effect. On the contrary, PhotoScan models may contain some holes, which are not present in other software tools such as VisualSFM and MicMac. ...
Article
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A system designed and developed for the three-dimensional (3-D) reconstruction of cultural heritage (CH) assets is presented. Two basic approaches are presented. The first one, resulting in an "approximate" 3-D model, uses images retrieved in online multimedia collections; it employs a clustering-based technique to perform content-based filtering and eliminate outliers that significantly reduce the performance of 3-D reconstruction frameworks. The second one is based on input image data acquired through terrestrial laser scanning, as well as close range and airborne photogrammetry; it follows a sophisticated multistep strategy, which leads to a "precise" 3-D model. Furthermore, the concept of change history maps is proposed to address the computational limitations involved in four-dimensional (4-D) modeling, i.e., capturing 3-D models of a CH landmark or site at different time instances. The system also comprises a presentation viewer, which manages the display of the multifaceted CH content collected and created. The described methods have been successfully applied and evaluated in challenging real-world scenarios, including the 4-D reconstruction of the historic Market Square of the German city of Calw in the context of the 4-D-CH-World EU project.
... Quadcopter UAVs are being used in many practical applications such as data collection [1], [2], crop spraying pesticide in agriculture [3], [4], search and rescue tasks [5], [6], payload carrying [7], [8], disaster management [9], [10], and military operations [11], [12]. As the technological development of computers, electronics, mechanics, control theories and communication technologies, the UAVs will become more and more maneuverable and smarter. ...
Article
Full-text available
An effective robust adaptive sliding mode controller to reject time-varying disturbances and uncertainties for improving the tracking performance of attitude and altitude control of quadcopter Unmanned Aerial Vehicles (UAVs) is presented in this paper. The flight controller provides a strict robustness, fast response, and rapid adaptation for the vehicle under the undesirable effect of perturbations. The proposed controller design is based on the super-twisting algorithm for excellently eliminating the chattering effect. In addition, an efficient adaptive law is achieved from the Lyapunov stability to ensure that the controller gains can be automatically adjusted to compensate for any effect of perturbations. Thus, the proposed algorithm greatly guarantees the robust control for the vehicles even without knowing the upper bound of a time-varying disturbance. A numerical simulation was executed and compared with recently alternative methods. A superior stability and excellent tracking performance of the attitude and altitude control of a quadcopter UAV in the simulation results demonstrated the effectiveness of the proposed method.
Article
In this paper, we investigate an unmanned aerial vehicle (UAV)-enabled full-duplex relaying system. By assuming that the UAV follows a circular trajectory and applies decode-and-forward relaying strategy, we study the joint design of beamforming and power allocation to maximize the instantaneous data rate, under both the individual and the sum power constraints over the source and relay nodes. As the problem is non-convex, we propose an efficient sub-optimal solution based on block-coordinate descent method by decomposing the problem into two sub-problems: a beamforming optimization sub-problem with given power allocation and a power allocation sub-problem with fixed beamforming. For the beamforming design sub-problem, the optimal solution is obtained based on the semi-definite relaxation technique. For low-complexity implementation, we also propose two sub-optimal designs based on transmit zero-forcing/ maximum ratio combing and maximum ratio transmission/ receive zero-forcing. For the power allocation sub-problem, the optimal solution is obtained in closed form. Then, closed form cumulative distribution function and outage probability expressions for sub-optimal beamforming with both uniform power allocation and optimal power allocation are derived. In addition, simple and informative high signal-to-noise ratio (SNR) approximations for outage probability expressions are presented to gain insights, in terms of diversity order, average SNR and relations between outage probability and UAV position. We show that the proposed power allocation does not affect the diversity order but it increases the average SNR, and hence reduces the outage probability in the high SNR regime. The optimal flying altitude that minimizes the average outage probability can be obtained via a one-dimensional search. The fixed wing UAV based mobile relay following a circular trajectory is much more energy efficient than the rotary wing UAV based static relay hovering at a fixed location.
Chapter
Although high quality 3D representations of important cultural landmarks can be obtained via sophisticated photogrammetric techniques, their demands in terms of resources and expertise pose limitations on the scale at which such approaches are used. In parallel, the proliferation of multimedia content posted online creates new possibilities in terms of the ways that such rich content can be leveraged, but only after addressing the significant challenges associated with this content, including its massive volume, unstructured nature, and noise. In this chapter, two strategies are proposed for using multimedia content for 3D reconstruction: an image-based approach that employs clustering techniques to eliminate outliers and a video-based approach that extracts key frames via a summarization technique. In both cases, the reduced and outlier-free image data set is used as input to a structure from motion framework for 3D reconstruction. The presented techniques are evaluated on the basis of the reconstruction of two world-class cultural heritage monuments.
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Rapid assessment of building damages due to natural disasters is a critical element in disaster management. Although airborne-based remote sensing techniques have been successfully applied in many postdisaster scenarios, automated building component-level damage assessment with terrestrial/mobile LiDAR data is still challenging to achieve due to lack of reliable segmentation methods for damaged buildings. In this research, a novel building segmentation and damage detection approach is proposed to realize automated component-level damage assessment for major building envelop elements including wall, roof, balcony, column, and handrail. The proposed approach first conducts semantic segmentation of building point cloud data using a rule-based approach. The detected building components are then evaluated to determine if the components are damaged. The authors applied this method on a mobile LiDAR data set collected after Hurricane Sandy. The results demonstrate that the approach is capable of achieving 96% and 86% parsing accuracy for wall façades and roof facets, and obtain 82% and 78% of detection accuracy for damaged walls and roof facets.
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Damage due to age or accumulated effects from hazards on existing structures poses a worldwide problem. In order to evaluate the current status of aging, deteriorating and damaged structures, it is vital to accurately assess the present conditions. It is possible to capture the in situ condition of structures by using laser scanners that create dense three-dimensional point clouds. This paper investigates the use of high resolution three-dimensional terrestrial laser scans coupled with images to capture geometric range data of complex scenes for surface damage detection and quantification. Although using images with varying resolution to detect cracks is an extensively researched topic, damage detection using laser scanners with and without color images is a new research area that holds many opportunities for enhancing the current practice of visual inspections. Thus, this paper mainly focuses on combining the best features of laser scans and images to create an automatic and effective surface damage detection method, which will reduce the need for skilled labor during visual inspections and allow automatic documentation of related information. A novel surface normal-based damage detection and quantification method that uses the local surface properties extracted from laser scanner data along with color information is presented. Color data provides information in the fourth dimension that enables detecting damage types such as cracks, corrosion, and related surface defects that are generally difficult to identify using only laser scanner.
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This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while achieving near real-time performance.
INACHUS: Integrated Wide Area Situation Awareness and Survivor Localisation in Search and Rescue Operations
  • G Athanasiou
G. Athanasiou et al., "INACHUS: Integrated Wide Area Situation Awareness and Survivor Localisation in Search and Rescue Operations," GiT4NDM 2015, Al Ain, UAE, 2015.