Architectural Building Detection and Tracking in Video Sequences Taken by Unmanned Aircraft System （UAS）

An Unmanned Aircraft System （UAS） is an aircraft or ground station that can be either remote controlled manually or is capable of flying autonomously under the guidance of pre-programmed Global Positioning System （GPS） waypoint flight plans or more complex onboard intelligent systems. The UAS aircrafts have recently found extensive applications in military reconnaissance and surveillance, homeland security, precision agriculture, fire monitoring and analysis, and other different kinds of aids needed in disasters. Through surveillance videos captured by a UAS digital imaging payload over the interest areas, the corresponding UAS missions can be conducted. In this paper, the authors present an effective method to detect and extract architectural buildings under rural environment from UAS video sequences. The SIFT points are chosen as image features. The planar homography is adopted as the motion model between different image frames. The proposed algorithm is tested on real UAS video data.

Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft

The architecture and working principle of coordinated search and rescue system of unmanned/manned aircraft,which is composed of manned/unmanned aircraft and manned aircraft,were first introduced,and they can cooperate with each other to complete a search and rescue task.Secondly,a threat assessment method based on meteorological data was proposed,and potential meteorological threats,such as storms and rainfall,can be predicted by collecting and analyzing meteorological data.Finally,an experiment was carried out to evaluate the performance of the proposed method in different scenarios.The experimental results show that the coordinated search and rescue system of unmanned/manned aircraft can be used to effectively assess meteorological threats and provide accurate search and rescue guidance.

Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

Unmanned Aircraft Systems(UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management(ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider(ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to:(A) describe what typical ANSP-supplied UAS Traffic Management(UTM) architecture is required to facilitate all types of civil UAS operations;(B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace;(C) outline future directions and challenges related with UAS operations for the ANSP.

Communication Scheduling with Diversity for Unmanned Aircraft Systems Using Local 5G

The use of unmanned aircraft systems(UAS)for critical public service missions by public organizations,local governments,and social users is expanding.Robust radio transmission by unmanned aerial vehicles(UAVs)is indispensable in these applications.One of the standards suitable for UAV wireless communications is local 5G.However,to introduce local 5G into a UAS,several problems specific to UASes must be solved.Challenges include the deterioration of the signal-to-noise ratio due to topography and obstacles,the uncertainty of the communication environment due to the movement of multiple UAVs,and the limitation of the frequency bandwidth.To address these problems and to introduce local 5G into the UAS,we propose a novel communication scheduling method.The method incorporates transmission modes with diversity.Our evaluations shows that total data volumes increase by 1.9~3 times with the proposed scheduling method compared with transmission without diversity or efficient scheduling.

Simulation Analysis of Electromechanical Coupling for Unmanned Aerial Vehicle Cabin Door System

In order to study the dynamic response of the unmanned aerial vehicle cabin door opening and closing system under impact load conditions, considering the flexible treatment of mechanical components, and the system’s motion with different stiffness of energy-absorbing components, a rigid-flexible coupling model of the cabin door actuation system was established in LMS. Virtual. Motion. In Amesim, a control model of the motor was created. Through the Motion-Amesim co-simulation module, the dynamic module of the system was combined with the motor control module to complete the electromechanical coupling simulation and analyze the results. .

Theoretical Investigations on Mapping Mean Distributions of Particulate Matter,Inert,Reactive,and Secondary Pollutants from Wildfires by Unmanned Air Vehicles(UAVs)

Evaluated Weather Research and Forecasting model inline with chemistry (WRF/Chem) simulations of the 2009 Crazy Mountain Complex wildfire in Interior Alaska served as a testbed for typical Alaska wildfire-smoke conditions. A virtual unmanned air vehicle (UAV) sampled temperatures, dewpoint temperatures, primary inert and reactive gases and particular matter of different sizes as well as secondary pollutants from the WRF/Chem results using different sampling patterns, altitudes and speeds to investigate the impact of the sampling design on obtained mean distributions. In this experimental design, the WRF/Chem data served as the “grand truth” to assess the mean distributions from sampling. During frontal passage, the obtained mean distributions were sensitive to the flight patterns, speeds and heights. For inert constituents mean distributions from sampling agreed with the “grand truth” within a factor of two at 1000 m. Mean distributions of gases involved in photochemistry differed among flight patterns except for ozone. The diurnal cycle of these gases’ concentrations led to overestimation (underestimation) of 20 h means in areas of high (low) concentrations as compared to the “grand truth.” The mean ozone distribution was sensitive to the speed of the virtual UAV. Particulate matter showed the strongest sensitivity to the flight patterns, especially during precipitation.

Research on Operation of UAVs in Non-isolated Airspace

In order to explore the safe operation of UAVs in non-segregated airspace,a collision risk model for cylindrical UAVs based on conflict areas was constructed and the risk of conflict between manned and unmanned aerial vehicles was researched.According to the results of risk analysis,a strategy for solving the conflict of aircraft is proposed,and the risk assessment experiment of unmanned aerial vehicle(UAV)in non-isolated airspace conflict is carried out.The results show that under the experimental conditions,large unmanned aerial vehicles equipped with ADS-B,TCAS and other airborne sensing systems will indeed interfere with other aircraft in airspace when they enter non-isolated airspace.Especially when the number of aircraft in airspace is large,the automatic avoidance system of UAV will increase the avoidance time and trigger the safety alarm,but the safety level is still acceptable.This indicates that it is relatively safe for UAVs to enter non-isolated airspace under limited conditions.The results can be used as a reference for the safe operation of unmanned aerial vehicle(UAV)in non-isolated airspace.

An Iterative Pose Estimation Algorithm Based on Epipolar Geometry With Application to Multi-Target Tracking

This paper introduces a new algorithm for estimating the relative pose of a moving camera using consecutive frames of a video sequence. State-of-the-art algorithms for calculating the relative pose between two images use matching features to estimate the essential matrix. The essential matrix is then decomposed into the relative rotation and normalized translation between frames. To be robust to noise and feature match outliers, these methods generate a large number of essential matrix hypotheses from randomly selected minimal subsets of feature pairs, and then score these hypotheses on all feature pairs. Alternatively, the algorithm introduced in this paper calculates relative pose hypotheses by directly optimizing the rotation and normalized translation between frames, rather than calculating the essential matrix and then performing the decomposition. The resulting algorithm improves computation time by an order of magnitude. If an inertial measurement unit(IMU) is available, it is used to seed the optimizer, and in addition, we reuse the best hypothesis at each iteration to seed the optimizer thereby reducing the number of relative pose hypotheses that must be generated and scored. These advantages greatly speed up performance and enable the algorithm to run in real-time on low cost embedded hardware. We show application of our algorithm to visual multi-target tracking(MTT) in the presence of parallax and demonstrate its real-time performance on a 640 × 480 video sequence captured on a UAV. Video results are available at https://youtu.be/Hh K-p2 h XNn U.

Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-Altitude Airspace with Geofence

In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System(UAS)in Unmanned Aircraft System Traffic Management(UTM),an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation(CSDTHE-IBTPS)algorithm is proposed.Firstly,an intent inference method of UAS is constructed based on the information of ADS-B and geofence system.Moreover,a geofence layering algorithm is proposed.Secondly,the Flight Mode Change Points(FMCP)are used to define the relevant mode transition parameters and design the guard conditions,so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition model.After that,the constrained Kalman filter(CKF)is applied to improve State-dependent-transition Hybrid Estimation(SDTHE)algorithm by applying equality constraint to the velocity of UAS in the straight phase and turning phase,respectively,and thus the constrained state-dependent-transition hybrid estimation(CSDTHE)algorithm is constructed.Finally,the results of intent inference and hybrid estimation are used to make trajectory prediction.Furthermore,each flight segment of trajectory is smoothed respectively by Rauch-Tung-Striebel(RTS)backward smooth method using the proposed CSDTHE-RTS algorithm,so as to obtain more accurate trajectory prediction results.The simulation shows that the proposed algorithm can reduce the errors of trajectory prediction and the time delay of intent inference.

Tactical conflict resolution in urban airspace for unmanned aerial vehicles operations using attention-based deep reinforcement learning

Unmanned aerial vehicles(UAVs)have gained much attention from academic and industrial areas due to the significant number of potential applications in urban airspace.A traffic management system for these UAVs is needed to manage this future traffic.Tactical conflict resolution for unmanned aerial systems(UASs)is an essential piece of the puzzle for the future UAS Traffic Management(UTM),especially in very low-level(VLL)urban airspace.Unlike conflict resolution in higher altitude airspace,the dense high-rise buildings are an essential source of potential conflict to be considered in VLL urban airspace.In this paper,we propose an attention-based deep reinforcement learning approach to solve the tactical conflict resolution problem.Specifically,we formulate this task as a sequential decision-making problem using Markov Decision Process(MDP).The double deep Q network(DDQN)framework is used as a learning framework for the host drone to learn to output conflict-free maneuvers at each time step.We use the attention mechanism to model the individual neighbor's effect on the host drone,endowing the learned conflict resolution policy to be adapted to an arbitrary number of neighboring drones.Lastly,we build a simulation environment with various scenarios covering different types of encounters to evaluate the proposed approach.The simulation results demonstrate that our proposed algorithm provides a reliable solution to minimize secondary conflict counts compared to learning and non-learning-based approaches under different traffic density scenarios.

Performance evaluation of a multi-rotor unmanned agricultural aircraft system for chemical application

Unmanned agricultural aircraft system(UAAS)hasbeen widely employed as a low-cost and reliable method to apply agrochemicals to small agricultural fields in China.The performance of battery-poweredmultirotor UAAS has attracted considerable attention from manufacturers and researchers.The objective of this research was to design a UAAS equippingwith a data acquisition system,to characterize its chemical application performance based on droplet deposition data and optimize the operating parameters.Each test was repeated three times to assess the reliability of the spraying system.Various flight parameters were also evaluated.The optimal spray pressure for the XR8001 and XR8002(TeeJet,Wheaton,IL,USA)nozzles was found to be 300 kPa,and the latter nozzle had a higher droplet deposition rate and spray volume.Spray volume was not significantly affected by the flight speed or droplet density and was negatively correlated with the nozzle pressure.The results of this study provide a basis for improving the efficiency of UAAS chemicalapplication systems in terms of large-scale application.

GREENSKY:A fair energy-aware optimization model for UAVs in next-generation wireless networks

Unmanned Aerial Vehicles(UAVs)offer a strategic solution to address the increasing demand for cellular connectivity in rural,remote,and disaster-hit regions lacking traditional infrastructure.However,UAVs’limited onboard energy storage necessitates optimized,energy-efficient communication strategies and intelligent energy expenditure to maximize productivity.This work proposes a novel joint optimization model to coordinate charging operations across multiple UAVs functioning as aerial base stations.The model optimizes charging station assignments and trajectories to maximize UAV flight time and minimize overall energy expenditure.By leveraging both static ground base stations and mobile supercharging stations for opportunistic charging while considering battery chemistry constraints,the mixed integer linear programming approach reduces energy usage by 9.1%versus conventional greedy heuristics.The key results provide insights into separating charging strategies based on UAV mobility patterns,fully utilizing all available infrastructure through balanced distribution,and strategically leveraging existing base stations before deploying dedicated charging assets.Compared to myopic localized decisions,the globally optimized solution extends battery life and enhances productivity.Overall,this work marks a significant advance in UAV energy management by consolidating multiple improvements within a unified coordination framework focused on joint charging optimization across UAV fleets.The model lays a critical foundation for energy-efficient aerial network deployments to serve the connectivity needs of the future.

Influence of nozzle enabling strategy on spray deposition of crop protection unmanned aerial system

Proper nozzles arrangement is significant to improve spray deposition of crop protection unmanned aerial system(UAS).Besides fuselage structure,the control strategy is another nozzle location changing method when there are multiple sets of nozzles.A four-rotor crop protection UAS equipped with four centrifugal nozzles was used to conduct a field experiment in the rupturing stage of rice.Two sets of nozzles in the front and rear of the fuselage were enabled independently to investigate spray deposition,including spray coverage and droplet density on the sampling cards.Various nozzle rotating speeds and flight speeds were employed in the experiment to study the influence of nozzle location on the deposition.With different nozzle rotating speeds,the droplet spectrum could be controlled.The results show that the average coverage and average cumulative droplet density are negatively correlated with flight speed.Average droplet density is also negatively correlated with the droplet size.Spray deposition of front nozzles is significantly reduced compared with that of the rear nozzles under the same spray parameters,especially when the droplet size is too large or the flight speed is too fast.The reduction is mainly concentrated in the center area of the spray swath.As a result,the average cumulative droplet density of the front nozzles decreases by 25.96%in total.The average droplet density decreases by 18.54%when the droplet size is smaller than 100μm,decreases by 25.02%when between 100μm and 200μm,and decreases by more than half when larger than 200μm.This research can provide guidance for the installation of UAS nozzles and spray control strategy design.

Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data.Here,we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean(Glycine max(L.)Merr.)varieties to identify previously uncharacterized loci.Specifically,we focused on the dissection of canopy coverage(CC)variation from this rich data set.We also inferred the speed of canopy closure,an additional dimension of CC,from the time-series data,as it may represent an important trait for weed control.Genome-wide association studies(GWASs)identified 35 loci exhibiting dynamic associations with CC across developmental stages.The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci(QTLs)detected in previous studies of adult plants and the identification of novel QTLs influencing CC.These novel QTLs were disproportionately likely to act earlier in development,which may explain why they were missed in previous single-time-point studies.Moreover,this time-series data set contributed to the high accuracy of the GWASs,which we evaluated by permutation tests,as evidenced by the repeated identification of loci across multiple time points.Two novel loci showed evidence of adaptive selection during domestication,with different genotypes/haplotypes favored in different geographic regions.In summary,the time-series data,with soybean CC as an example,improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.

A survey of safety separation management and collision avoidance approaches of civil UAS operating in integration national airspace system

Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System(UAS).As an emerging industry,the UAS industry has been attracting great attention from governments of all countries and the aviation industry.UAS are highly digitalized,informationized,and intelligent;therefore,their integration into the national airspace system has become an important trend in the development of civil aviation.However,the complexity of UAS operation poses great challenges to the traditional aviation regulatory system and technical means.How to prevent collisions between UASs and between UAS and manned aircraft to achieve safe and efficient operation in the integrated operating airspace has become a common challenge for industry and academia around the world.In recent years,the international community has carried out a great amount of work and experiments in the air traffic management of UAS and some of the key technologies.This paper attempts to make a review of the UAS separation management and key technologies in collision avoidance in the integrated airspace,mainly focusing on the current situation of UAS Traffic Management(UTM),safety separation standards,detection system,collision risk prediction,collision avoidance,safety risk assessment,etc.,as well as an analysis of the bottlenecks that the current researches encountered and their development trends,so as to provide some insights and references for further research in this regard.Finally,this paper makes a further summary of some of the research highlights and challenges.

Coordinated standoff tracking of moving targets using differential geometry

This research is concerned with coordinated standoff tracking, and a guidance law against a moving target is proposed by using differential geometry. We first present the geometry between the unmanned aircraft(UA) and the target to obtain the convergent solution of standoff tracking when the speed ratio of the UA to the target is larger than one. Then, the convergent solution is used to guide the UA onto the standoff tracking geometry. We propose an improved guidance law by adding a derivative term to the relevant algorithm. To keep the phase angle difference of multiple UAs, we add a second derivative term to the relevant control law. Simulations are done to demonstrate the feasibility and performance of the proposed approach. The proposed algorithm can achieve coordinated control of multiple UAs with its simplicity and stability in terms of the standoff distance and phase angle difference.

Low-altitude geophysical magnetic prospecting based on multirotor UAV as a promising replacement for traditional ground survey

The prospects for expanding the mineral resource base in many countries are linked with the exploration of stranded sites localized at unexplored areas with complex natural and landscape conditions that make any ground survey,including magnetic prospecting,difficult and expensive.The current level of geology requires high-precision and large-scale data at the first stages of geological exploration.Since 2012,technologies of aeromagnetic surveying with unmanned aircraft vehicles(UAV)enter the market,but most of them are based on big fixed-wing UAV and do not allow to substantially increase the level of survey granularity compared with traditional aerial methods.To increase the scale of survey,it is necessary to reduce the altitude and speed of flight,for which the authors develop the methodical and technical solutions described in this article.To obtain data at altitudes of 5 m above the terrain even in a rugged relief,we created heavy multirotor UAVs that are stable in flight and may be used in a wide range of environmental conditions(even a moderate snowfall),and develop a special software to generate flight missions on the basis of digital elevation models.A UAV has special design to reduce magnetic interference of the flight platform;the magnetic sensor is hung below the aircraft.This technology was conducted in a considerable amount of magnetic surveys in the mountainous regions of East Siberia between 2014 and 2016.The results of the comparison between airborne and ground surveys are presented,which show that the sensitivity of the developed system in conjunction with low-altitude measurements can cover any geologically significant anomalies of the magnetic field.An unmanned survey is cheaper and more productive;the multirotor-based technologies may largely replace traditional ground magnetic exploration in scales of 1:10,000−1:1000.

UAVs as remote sensing platforms in plant ecology:review of applications and challenges

Aims Unmanned aerial vehicles(UAVs),i.e.drones,have recently emerged as cost-effective and flexible tools for acquiring remote sensing data with fine spatial and temporal resolution.It provides a new method and opportunity for plant ecologists to study issues from individual to regional scales.However,as a new method,UAVs remote sensing applications in plant ecology are still challenged.The needs of plant ecology research and the application development of UAVs remote sensing should be better integrated.Methods This report provides a comprehensive review of UAV-based remote sensing applications in plant ecology to synthesize prospects of applying drones to advance plant ecology research.Important Findings Of the 400 references,59%were published in remote sensing journals rather than in plant ecology journals,reflecting a substantial gap between the interests of remote sensing experts and plant ecologists.Most of the studies focused on UAV remote sensing’s technical aspects,such as data processing and remote sensing inversion,with little attention on answering ecological questions.There were 61%of studies involved community-scale research.RGB and multispectral cameras were the most used sensors(75%).More ecologically meaningful parameters can be extracted from UAV data to better understand the canopy surface irregularity and community heterogeneity,identify geometrical characteristics of canopy gaps and construct canopy chemical assemblies from living vegetation volumes.More cooperation between plant ecologists and remote sensing experts is needed to promote UAV remote sensing in advancing plant ecology research.

Chattering-free sliding mode control with unidirectional auxiliary surfaces for miniature helicopters

Purpose-This article proposes a chattering-free sliding mode control scheme with unidirectional auxiliary surfaces(UAS-SMC)for small miniature autonomous helicopters(Trex 250).Design/methodology/approach-The proposed UAS-SMC scheme consists of a nested sequence of rotor dynamics,angular rate,Euler angle,velocity and position loops.Findings-It is demonstrated that the UAS-SMC strategy can eliminate the chattering phenomenon exhibiting in the convenient SMC method and achieve a better approaching speed.Originality/value-The proposed control strategy is implemented on the helicopter and flight tests clearly demonstrate that a much better performance could be achieved,compared with convenient SMC schemes.

Parameters optimization of crop protection UAS based on the first industry standard of China

The effective swath width(ESW)and the droplet penetration rate(DPR)directly affect the spraying quality,the spraying efficiency and the control effect of pests and diseases during the crop protection unmanned aircraft system(CPUAS)application.However,the ESW and DPR are not constant with the changes of the flight speed(FS)and the flight height(FH).In order to investigate the ESW and DPR of the CPUAS P20,four levels of FS(3 m/s,4 m/s,5 m/s and 6 m/s)and three levels of FH(1.5 m,2.0 m and 2.5 m)experiments were carried out according to the first industry standard of China for the CPUAS in the wheat field.The results demonstrated that the ESWs were negatively correlated with the FS and the FH.Most of the ESWs were over 2 m in the 12 treatments,in which the maximum one was 3.25 m(3 m/s,1.5 m).The DPRs were negatively correlated with the FH under the same FS,the average value of the DPRs was 48.37%,in which the maximum one was 78.34%(4 m/s,1.5 m)and the minimum one was 25.5%(6.0 m/s,2.5 m).The statistical analyses showed that the FS had significant impacts on the ESWs(0.01<p-value<0.05)while there were no significant differences among different FH treatments(p-value>0.05).The impacts of both FS and FH on the DPRs were extremely significant(p-value<0.01),and the interactive impacts were significant(0.01<p-value<0.05).Therefore,it is concluded that reducing the FS could increase the ESWs,and reducing the FH could increase the DRPs at the same FS.In conclusion,the maximum spraying efficiency of P20 was 4.342 hm2/h with 6 m/s FS and 1.5 m FH in case of satisfying the requirement of DPRs.This study provided scientific references for guiding the CPUAS spraying.