Area Reconnaissance Research Articles

Vulnerability Assessment and Topology Reconstruction of Task Chains in UAV Networks

With the increasing complexity of environments and the diversity of task chains, individual unmanned aerial vehicles (UAVs) often struggle to satisfy the demands of task chains, including load capacity improvement, information perception, and information procession. In complex task chains involving various UAVs, such as area reconnaissance and fire rescue, any attack on critical UAVs can greatly disrupt the execution of the entire task chain by causing equipment damage or connectivity disruption. To ensure network resilience post attack, identifying vulnerable nodes in the UAV network becomes crucial. In this paper, a Vulnerability-based Topology Reconstruction Mechanism (VUTRM) is proposed to rank the importance of nodes in task chains and formulate a topology reconstruction. It consists of two parts: the first part is a Multi-metric Node Vulnerability Assessment Algorithm (MENVAL) used to rank the importance of nodes in task chains, and the second part is a Node Importance-based Topology Reconstruction Algorithm (NITRA) used to reconstruct the UAV network with the obtained node ranking. Finally, simulations carried out with simulation software demonstrate that our proposed method accurately identifies network vulnerabilities and promptly implements effective reconstruction measures to minimize network damage.

Area reconnaissance modeling of modular reconnaissance robotic systems

Area reconnaissance modeling of modular reconnaissance robotic systems

Integrate Assignment of Multiple Heterogeneous Unmanned Aerial Vehicles Performing Dynamic Disaster Inspection and Validation Task With Dubins Path

The actual performance of a task assignment method of unmanned aerial vehicles (UAVs) shows a considerable dependence on the path planning process coupled with it; however, this topic has been rarely studied in the existing literature. This paper considers the problem of maximizing the task-assignment reward of a fleet of heterogeneous UAVs for a dynamic reconnaissance and confirmation task under constraints of critical time and multi-UAV tasks where the coupled path optimization objectives also need to be considered. The existing consensus-based bundle algorithm is extended with an effective method for managing the multi-task and multi-agent constraints. The proposed method can optimize the inherent coupling path using the Dubins path to reduce the differences between the estimated path and the actual path, shortening the operation time by adopting the distributed genetic algorithm. The proposed method is verified by the sample run tests of a disaster area reconnaissance and confirmation task and Monte Carlo comparison simulations with the two existing algorithms. The results verify both the practicality and advantages of the proposed method.

PDP-CNN: A Deep Learning Model for Post-Hurricane Reconnaissance of Electricity Infrastructure on Resource-Constrained Embedded Systems at the Edge

Unmanned aerial vehicles (UAVs) equipped with cameras have provided new capabilities for the reconnaissance of disaster-stricken areas. Deep learning-based computer vision algorithms enable the analysis of the captured images and the detection of damage to the built environment. If such analyses are conducted onboard in UAVs, they will provide real-time actionable information that is critical for the accelerated restoration of systems. However, conventional deep learning algorithms are computationally demanding. Moreover, the deployment of deep learning models with a large number of parameters in scenarios that require low-latency inference is prohibitive. To address this fundamental gap, we develop an efficient deep learning-based computer vision model of power distribution poles (PDPs) damage detection that is capable of onboard deployment in UAVs. Specifically, we propose a lightweight convolutional neural network (CNN) architecture called PDP-CNN that embodies multiscale feature operations and anchor-less object detection. This model is applied to a dedicated image database from a post-hurricane reconnaissance in PDPs. Results of extensive experiments show that PDP-CNN is capable of achieving high throughput, competitive accuracy, and efficient memory utilization on power-constrained embedded systems.

Features of the Implementation of technological Solutions of the Bridge Crossing Construction Project with a Temporary Bridge

Purpose. The main aim of the research is the study of the methodology of conducting engineering and technical reconnaissance and the implementation of structural and technological solutions for the project of the construction of a bridge crossing with a temporary bridge damaged as a result of hostilities. Methodology. The achievement of the set goal involves research and analysis of practical structural and technological solutions for construction works, restoration of bridge crossings with temporary bridges, as well as study and generalization of practical experience of implemented technological solutions of combining wooden typical structures with steel typical span structures. Findings. A generalization of the experience of conducting engineering and technical reconnaissance in construction areas, restoration of bridge crossings in de-occupied territories was generalized. The author revealed and clarified the general key stages of the implementation of technological solutions for the project of the construction of a bridge crossing with a temporary bridge damaged as a result of hostilities using a combination of steel inventory bridge structures with wooden bridge structures. Originality. For the first time, the author investigated the peculiarities of conducting engineering and technical reconnaissance in order to implement the obtained results in the relevant project documentation for the construction of a temporary bridge. The peculiarities of constructive and technological solutions with a rational combination of various materials and structures during the construction of temporary bridges, which ensure a long period of their operation, are considered. Practical value. The elements of the methodology of organization and carrying out engineering technical exploration of terrain, water obstacles, construction sites and the base of logistics and other measures will contribute to the quality preparation of project documentation for the construction of bridge crossings with temporary bridges. The application peculiarities of non-standard projects of conducting works and structural and technological solutions in the construction of temporary bridges have a number of technological advantages that make it possible to ensure effective restoration of the destroyed combat actions of the bridges in a short time. Some technological methods of combinations of wooden structures and elements with steel carriers of the roadway when building temporary car bridges increase their load capacity.

The Satellite Coverage Analysis is Based on a Combination of STK and MATLAB

In maritime military operations, reconnaissance satellites can provide all-around and efficient reconnaissance and surveillance of target areas in established orbits, regardless of territorial, airspace, and territorial sea restrictions, and are a beneficial means of leadership in today's military. STK can construct satellite motion models, and MATLAB can invoke the STK function module to achieve complex scene generation. The two are combined, respectively, with Walk Constellation grouping and single-satellite simulation of specific target areas at sea, resulting in coverage analysis reports with good results.

The Experimental Study of Attitude Stabilization Control for Programmable Nano Quadcopter

Rotary-wing nano-quadcopters are unmanned technologies used for reconnaissance and surveillance operations in many areas, especially strategic missions such as security and military operations. The main problem for these devices, which reached a wide audience with the widespread use of civilian production, is stabilization. The most important parameter affecting the stable, effective and reliable flight of these UAVs in the air is PID elements. In this study, experimental studies are carried out in [x, y, z] coordinates using a programmable Nano-quadcopter Crazyflie 2.0 drone. In order to determine the relationship between stabilization and PID control parameters of these systems, each coordinate axis is analyzed statistically. As far as is known, there is no study in the literature regarding the performance of the PID parameters of the Crazyflie 2.0 drone. At the end of the analysis study with the SPSS program, it is determined that the related drone moves with a very high level of efficiency in the "z" axis and performs the task related to the high level of efficiency on the y-axis. It is also confirmed that the drone performs poorly in the stabilization movement on the "x" axis and as a result of the analysis study, the system becomes more stable by making the necessary adjustments in the "yaw_p" parameter. Thanks to the study, it is aimed to create a decision support system for the optimization of the PID control parameters of UAVs, which are used extensively in every sector.

Undercover karst imaging using a Fuzzy c-means data clustering approach (Costa Brava, NE Spain)

Identification of undercover karst areas can be essential for engineering or hydrogeological studies. Geological reconnaissance of karst areas can be challenging due to their complex and highly heterogeneous internal structure. Herein, we present a case study carried out at the carbonate coastal Montgrí Massif in Costa Brava (Spain), which, in the study area, is characterized by a well-developed karst system covered by Quaternary sediments. The objectives of the work are to delineate and characterize karst structures using geophysical techniques and to produce a subsurface geological model that goes beyond the individual physical properties determined independently by each geophysical method. We acquired electrical resistivity and seismic datasets for five collocated profiles. We analyzed the seismic datasets to retrieve P-wave (Vp) and S-wave (Vs) velocity models. Clay-filled karst formations may produce seismic and electrical signatures that are difficult to interpret due to the wide range of values that can be present depending on the properties of the karst's infill. In this type of environment, the Fuzzy c-means (FCM) data clustering approach is a way of producing an integrated model that can help to constrain the lithological interpretation. In this study, FCM is first applied to an electrical resistivity-Vs dataspace in order to characterize near surface sediments. Four different groups are recognized corresponding to different lithologies, fluid conductivities, and saturations in the unconsolidated sediments. Secondly, FCM analysis of the resistivity-Vp datasets provides integrated models that help to delineate the karst areas. The interpretive constraints used derive from the results of the first FCM application and the lithological description of a single borehole that reaches the karst below the Quaternary sediments. In this way, karst is identified in all five profiles. This study shows that the integration of seismic and electrical resistivity information using the FCM approach can extend borehole information throughout the study area and thus provide comprehensive geological models in karst environments.

UAV Path Planning for Reconnaissance and Look-Ahead Coverage Support for Mobile Ground Vehicles.

Path planning of unmanned aerial vehicles (UAVs) for reconnaissance and look-ahead coverage support for mobile ground vehicles (MGVs) is a challenging task due to many unknowns being imposed by the MGVs’ variable velocity profiles, change in heading, and structural differences between the ground and air environments. Few path planning techniques have been reported in the literature for multirotor UAVs that autonomously follow and support MGVs in reconnaissance missions. These techniques formulate the path planning problem as a tracking problem utilizing gimbal sensors to overcome the coverage and reconnaissance complexities. Despite their lack of considering additional objectives such as reconnaissance coverage and dynamic environments, they retain several drawbacks, including high computational requirements, hardware dependency, and low performance when the MGV has varying velocities. In this study, a novel 3D path planning technique for multirotor UAVs is presented, the enhanced dynamic artificial potential field (ED-APF), where path planning is formulated as both a follow and cover problem with nongimbal sensors. The proposed technique adopts a vertical sinusoidal path for the UAV that adapts relative to the MGV’s position and velocity, guided by the MGV’s heading for reconnaissance and exploration of areas and routes ahead beyond the MGV sensors’ range, thus extending the MGV’s reconnaissance capabilities. The amplitude and frequency of the sinusoidal path are determined to maximize the required look-ahead visual coverage quality in terms of pixel density and quantity pertaining to the area covered. The ED-APF was tested and validated against the general artificial potential field techniques for various simulation scenarios using Robot Operating System (ROS) and Gazebo-supported PX4-SITL. It demonstrated superior performance and showed its suitability for reconnaissance and look-ahead support to MGVs in dynamic and obstacle-populated environments.

An outbreak of krait bite amongst people in the desert sands: the cryptic enemy within

Background: Snake bite has been associated with high morbidity and mortality. Personnel are at high risk of snake bite. This investigation was carried out amongst residents with the purpose of identifying the factors that led to the bites and recommending preventive measures.Methods: Three cases bitten by a single snake were investigated retrospectively. Historical data was collected and area reconnaissance was done. The severity of envenomation was assessed using a graded scale. Local authorities were briefed on remedial measures to prevent snake bite cases in future.Results: The three cases of snake bite were rushed to the Primary health centre for first aid. Local signs of envenomation were absent in all cases. Two cases died before reaching the hospital. The third case managed to reach the hospital and was administered anti snake venom and put on ventilatory support, following which he recovered. Absence of local signs, along with the neurotoxic features led to the conclusion that the bite was caused by a krait. Environmental survey revealed that the village was surrounded with thick vegetation, waste disposal was being done too close to the cookhouse and snake trenches were not dug up.Conclusions: The key for preventing fatality in snake bite is the immediate transfer of the victim to the nearest hospital equipped with anti-snake venom and ventilatory support equipment.

Karst Sinkhole Detecting and Mapping Using Airborne LiDAR - A Conceptual Framework

Sinkholes cause subsidence and collapse problems for many transportation infrastructure assets. Subsequently, transportation infrastructure management agencies dedicate a considerable amount of time and money to detect and map sinkholes as part of their asset management programs. Traditionally, sinkholes are detected through area reconnaissance, which includes visual inspection of a site to locate existing sinkholes or device inspection of a site to locate potential sinkholes or previously filled sinkholes. Another method for sinkhole detection is through a review of maps such as geological maps. These methods are expensive, time-consuming, and labor-intensive. Recent advances in remote sensing, especially airborne light detection and ranging (LiDAR), allows for the examination of the change in the Earth's surface elevation accurately and rapidly. The focus of this study is to develop a conceptual framework for sinkhole detection and mapping with airborne LiDAR. This conceptual framework lays the foundation for the future application of airborne LiDAR for sinkhole detection and mapping.

Chemical accident area reconnaissance by unmanned aircraft

Chemical accidents, as unexpected events, occur in contemporary society relatively often, and the resulting consequences can be different - from very small to catastrophic. Within the integrated response to chemical accidents, chemical reconnaissance of the accident area takes a significant place. This paper presents the possibility of prioritizing the criteria and attributes of the criterion for selecting unmanned aircraft for reconnaissance of the chemical accident area. By analyzing the content of the available literature, the criteria for evaluating the alternatives of the offered 'miniunmanned aircraft' are set out. This paper deals with testing using the questionnaire, processing the obtained data and prioritization of the criteria and attributes using the fuzzy AHP method and examination of the results consistency by the consistency degree. Testing of the obtained results and selection of optimal unmanned aircraft using the TOPSIS method has been carried out, as well. Due to the extreme danger that personnel are exposed to during the chemical reconnaissance of the accident area (high concentrations of dangerous chemicals, long-term wearing of protective equipment, increased psychophysical stress, etc.), this paper considers the possibility of using unmanned aircraft. Furthermore, this paper suggests the way of selecting optimal UA as an element for reconnaissance in a particular chemical accident.

Replication of human operators’ situation assessment and decision making for simulated area reconnaissance in wargames

This paper describes a replication model of human operators’ situation assessment and decision making in a simulated area reconnaissance wargame. A variety of factors that affect human operators’ threat assessment and decision making were identified and categorized based on interviews with Subject Matter Experts and a review of defense doctrine on area reconnaissance. By combining these factors with the capabilities of existing synthetic environments, a schema consisting of a set of Bayesian networks and associated joint probability distributions for human operators’ situation assessment and decision making was developed. To verify and validate the proposed schema, a software system was designed and implemented, and then used for analyzing the consistency between the replicator’s decisions and human players’ decisions. Results showed that the proposed approach replicated human operators’ situation assessment and movement-based decision making in the wargame with high consistency.

SURF 기법을 활용한 위성 SAR 다중해상도 영상의 정합 및 기하보정

위성 SAR 영상의 활용이 증가하면서 영상의 해석 및 융합을 위한 정밀 기하보정에 대한 필요성이 높아지고 있다. 특히 광역감시 목적으로 활용되기 위해 서로 다른 해상도를 갖는 SAR 영상간 정보융합도 활발해지고 있다. 일반적으로 SAR 영상의 기하보정은 위성의 궤도 및 자세정보를 활용하여 수행할 수 있지만 SAR 센서의 궤도 및 시스템 오차, 대상지형 특성에 의한 왜곡으로 인해 추가적인 보정이 필요하게 된다. SAR 영상을 통한 변화탐지나 타 영상과의 융합에 적용하기 위해서는 기하 오차 보정이 반드시 선행되어야 한다. 이를 위해 다수의 지상 기준점을 선정하고 이를 포함하는 기준 영상과 비교하여 원본 영상에서 대응점을 찾는 방식으로 정밀 기하보정을 수행할 수 있다. Speeded Up Robust Feature (SURF) 기법은 쉽고 빠르게 영상의 기준점을 찾을 수 있지만 상대적으로 해상도가 낮고 스펙클 잡음에 영향을 받는 SAR 영상에서는 활용하기가 어렵다고 알려져 있다. 본 논문에서는 SURF 기법을 위성 SAR 영상에 적용할 때 발생할 수 있는 오차를 추출하고 영상 특성에 따른 성능 변화를 분석하였다. SURF 알고리즘의 적용이 가능한 입력 변수의 적정 범위를 제시하고 그에 따른 영상 정합의 오차를 분석하여 중저해상도의 위성 SAR 영상에 대해서도 SURF 기법을 통한 기하 보정 및 영상 정합이 적용될 수 있음을 검증하였다. As applications of spaceborne SAR imagery are extended, there are increased demands for accurate registrations for better understanding and fusion of radar images. It becomes common to adopt multi-resolution SAR images to apply for wide area reconnaissance. Geometric correction of the SAR images can be performed by using satellite orbit and attitude information. However, the inherent errors of the SAR sensor's attitude and ground geographical data tend to cause geometric errors in the produced SAR image. These errors should be corrected when the SAR images are applied for multi-temporal analysis, change detection applications and image fusion with other sensor images. The undesirable ground registration errors can be corrected with respect to the true ground control points in order to produce complete SAR products. Speeded Up Robust Feature (SURF) technique is an efficient algorithm to extract ground control points from images but is considered to be inappropriate to apply to SAR images due to high speckle noises. In this paper, an attempt is made to apply SURF algorithm to SAR images for image registration and fusion. Matched points are extracted with respect to the varying parameters of Hessian and SURF matching thresholds, and the performance is analyzed by measuring the imaging matching accuracies. A number of performance measures concerning image registration are suggested to validate the use of SURF for spaceborne SAR images. Various simulations methodologies are suggested the validate the use of SURF for the geometric correction and image registrations and it is shown that a good choice of input parameters to the SURF algorithm should be made to apply for the spaceborne SAR images of moderate resolutions.

Automatic path generation for terrain navigation

Navigation in 3D terrain is considered to be a challenging task and requires virtual camera control skills such as zooming, panning and tilting. Novice users can easily get distracted and disorientated which may result in being lost in space. Solutions for the virtual environment exploration problems are still being researched in order to assist users during their journey inside virtual environments. Among these solutions, assisted camera control techniques require viewpoint computation and path planning. This paper introduces a novel approach to navigate over a 3D terrain using best viewpoints. We exploit the concept of Viewpoint Entropy for best view determination and use Greedy N-Best View Selection for visibility calculations. We integrate road network data to extract regions for detailed visibility analysis in subsections of the terrain. In order to connect the calculated viewpoints, we use an evolutionary programming approach for the Traveling Salesman problem. We present the generated tour using a Google Earth framework.The computed and planned viewpoints in our solution reduce human effort when used as starting points for scene exploration or to generate the representative images of the terrain dataset. The proposed framework can be integrated into 3D game engines or urban visualization systems. This integration gives quickly a glimpse or tour of the environment for novice users without the help of prior planning. Furthermore, terrain visibility used together with road network data and an optimization method for final path construction allows the computed path to be used for large urban area reconnaissance and surveillance tasks with aerial vehicles.

Interactive On-Site and Remote Damage Assessment for Urban Search and Rescue

Extraction of victims entrapped in collapsed structures is the objective of urban search and rescue (USAR) operations. Assessing the potential for live victims and the stability of partially or totally collapsed structures are critical aspects of such operations. This paper outlines relevant activities of the first USAR team arriving in Haiti after the January 2010 earthquake and the supporting actions of their home-base team. The purpose of this paper is to illustrate the different aspects of damage assessment and discuss how those aspects relate to overall USAR field operations. Guidelines developed for USAR teams are used to shed additional light on the concept of USAR-related damage assessment. Three broad types of considerations are found to constitute damage assessment, requiring varying levels of detail in damage descriptions: area reconnaissance, exterior structural evaluation, and interior structural-member evaluation. Using available information and communication technology, a home-base team can become an active player in area reconnaissance by providing pre- and post-impact information about the affected area to the USAR team.

Micro Air Vehicle Trajectory Planning in Winds

M ICRO aerial vehicles (MAVs) are small aerial vehicles, generallywith dimensions on the order of 1 ft (or 0.3m). Their small sizes often imply that their flight speeds are also small, roughly on the order of 20–60 km=h. MAVs come in a wide variety of forms, such as fixed wing, flapping wing, and rotary wing [1]. They are finding increasingly more applications in such areas as military missions, reconnaissance of hazardous or remote areas, and monitoring of indoor areas. Because of their small sizes and light weights, MAV flight trajectories are significantly susceptible to winds in general. For example, it is possible for the wind to be so strong that the MAV is unable to advance in certain directions. (This problem can be formulated in terms of the controllability of a point and its associated reachable set, see [2].) It is therefore necessary to develop a systematic approach toMAV trajectory generation that addresses the characteristic issues of MAV flights in winds. Specifically, the following three points must be considered: 1) Target points may not always be feasible due to winds. 2) Wind profiles may have significant effects on fuel costs (both desirable and undesirable). 3) Trajectory generation must always yield a feasible solution due to the absence of human operators. The main goal of this note is to study meaningful trajectory generation problem formulations for MAV trajectories in winds, to address all three of the issues discussed above that characterize MAV flights. Specifically, MAV flights in winds are formulated as nonlinear optimal control problems, with proper constraints on states and controls. In particular, the reaching of a target point is enforced via a penalty term in the performance index. Thus, while a target point is not necessarily reached, a flyable trajectory that is optimal under prevailing conditions is obtained. Both constant and position dependent wind is considered.

Evaluating reconnaissance CSEM survey designs using detection theory

Marine controlled-source electromagnetic (CSEM) surveys have recently found wide application for mapping resistive hydrocarbon reservoirs (Ellingsrud et al., 2002). Typically, these surveys have been target oriented and have been used to delineate potential reservoirs already mapped by other methods. However, CSEM surveys can also be used for reconnaissance in areas where no specific targets have been identified (Srnka et al., 2005). The objective of a reconnaissance CSEM survey is to detect the presence of resistive bodies that are large enough to be economic hydrocarbon reservoirs. These bodies would then be candidates for more detailed seismic or CSEM surveys.

A BEHAVIOUR-BASED NAVIGATION SYSTEM FOR AN AUTONOMOUS INDOOR BLIMP

This paper describes a behaviour-based navigation system for airborne autonomous robots. The work has been validated by controlling an indoor blimp with a finite-state machine. It is shown that behaviour-based navigation, especially concerning mobile robots for indoor applications, is predestined to perform reconnaissance of unknown areas and moreover for navigation tasks in familiar environment. Due to the inability of most autonomous indoor aerial vehicles to carry heavy sensors, these systems lack of metrical information and therefore the explicit localization is yet impossible until today. The behaviour-based navigation is combined with a variety of path-planning methods (tree-search, potential fields, etc.) using obstacle-maps of known surroundings enabling the robot to acquire a desired position in a correspondent cluster of rooms.

Market-based Multirobot Coordination for Complex Tasks

Current technological developments and application-driven demands are bringing us closer to the realization of autonomous multi-robot systems performing increasingly complex missions. However, existing methods of distributing mission subcomponents among multirobot teams do not explicitly handle the required complexity and instead treat tasks as simple indivisible entities, ignoring any inherent structure and semantics that such complex tasks might have. These task properties can be exploited to produce more efficient team plans by giving individual robots the ability to come up with new, more localized ways to perform a task; by allowing multiple robots to cooperate by sharing the subcomponents of a task; or both. In this paper, we describe the complex task allocation problem and present a distributed solution for efficiently allocating a set of complex tasks among a robot team. Complex tasks are tasks that can be solved in many possible ways. In contrast, simple tasks can be accomplished in a straightforward, prescriptive manner. The current scope of our work is currently limited to complex tasks that can be decomposed into multiple subtasks related by Boolean logic operators. Our solution to multirobot coordination for complex tasks extends market-based approaches by generalizing task descriptions into task trees, which allows tasks to be traded in a market setting at variable levels of abstraction. In order to incorporate these task structures into a market mechanism, novel and efficient bidding and auction clearing algorithms are required. As an example scenario, we focus on an area reconnaissance problem which requires sensor coverage by a team of robots over a set of defined areas of interest. The advantages of explicitly modeling complex tasks during the allocation process is demonstrated by a comparison of our approach with existing task allocation algorithms in this application domain. In simulation we compare the quality of solution and the computation times of these different approaches. Implementations on two separate teams of indoor and outdoor robots further validates our approach.