Small Unmanned Aerial Vehicle Flight Research Articles

Improving small unmanned aerial vehicle flight endurance with cryo-compressed hydrogen vessels

Detailed analysis indicates that substantial increases (22–43%) in flight endurance of small unmanned aerial vehicles (UAVs) powered by liquid hydrogen (LH2) are possible by increasing the maximum allowable pressure of the cryogenic storage vessel beyond the critical point to contain evaporated hydrogen (H2) and mitigate vent losses to the environment. Taking an existing UAV (US Naval Research Laboratory's “Ion Tiger”) as a baseline, we consider the effect of increasing Dewar maximum allowable pressure on flight endurance, under two different scenarios. In Case 1, the weight of the H2 storage system (including H2) is kept equal to the baseline design to maintain flight conditions unchanged. In Case 2, the external volume of the Dewar is kept equal to the baseline design, and the weight of the Dewar (and UAV) increases when the maximum allowable pressure increases, with the result that the propulsion power for the heavier UAV increases.The results are favorable. Although the modified Dewars have smaller inner volume (Case 1) or greater weight (Case 2) than the original Ion Tiger, flight endurance increases by 22% (Case 1) and 43% (Case 2), because the large H2 vent losses (39%) of the original design are reduced to only 1.6% (Case 1) and 1% (Case 2). The much higher utilization efficiency of the H2 stored in these modified Dewars compensates for their volume and weight disadvantages, resulting in UAVs with superior endurance.

Autonomous flight insurance method of unmanned aerial vehicles Parot Mambo using semantic segmentation data

Autonomous navigation of unmanned aerial vehicles (UAVs) has become in the past decade an extremely attracting topic, also due to the increasing availability of affordable equipment and open-source control and processing software environments. This demand has also raised a strong interest in developing accessible experimental platforms to train engineering students in the rapidly evolving area of autonomous navigation. In this paper, we describe a platform based on low-cost off-the-shelf hardware that takes advantage of the Matlab/Simulink programming environment to tackle most of the problems related to UAV autonomous navigation. More specifically, the subject of this paper is the autonomous control of the flight of a small UAV, which must explore and patrol an indoor unknown environment. Objectives: to analyse the existing hardware platforms for autonomous flight indoors, choose a flight exploration scenario of unknown premises, to formalize the procedure for obtaining a model of knowledge for semantic classification of premises, to formalize obtaining distance to obstacles using data camera horizontally employment and building on its barrier map. Namely, we use the method of image segmentation based on the brightness threshold, a method of training the semantic segmentation network, and computer algorithms in probabilistic robotics for mobile robots. We consider both the case of navigation guided by structural visual information placed in the environment, e.g., contrast markers for flight (such as path marked by a red tape), and the case of navigation based on unstructured information such as recognizable objects or human gestures. Basing on preliminary tests, the most suitable method for autonomous in-door navigation is by using\ object classification and segmentation, so that the UAV gradually analyses the surrounding objects in the room and makes decisions on path planning. The result of our investigation is a method that is suitable to allow the autonomous flight of a UAV with a frontal video camera. Conclusions. The scientific novelty of the obtained results is as follows: we have improved the method of autonomous flight of small UAVs by using the semantic network model and determining the purpose of flight only at a given altitude to minimize the computational costs of limited autopilot capabilities for low-cost small UAV models. The results of our study can be further extended by means of a campaign of experiments in different environments.

Small Unmanned Aerial Vehicle Flight Planning in Urban Environments

This work proposes a fast algorithm for generating obstacle-free and wind-efficient flight paths at a constant above-ground-level altitude in urban environments because a fast flight path planning algorithm is an essential function or service needed for enabling small unmanned aerial vehicle (sUAV) to operate in urban environments within Class G airspace. The proposed method first converts the 3D path planning problem to a 2D problem by constructing an obstacle map at a given above-ground-level altitude. A quad-tree decomposition is then used to build a search space in terms of obstacle occupancy and wind difference. The wind cost of traveling through each cell is defined based on energy consumption under various wind conditions. A repulsive potential is also adopted to make sure that the flight plans stay away from obstacles. The Theta* search algorithm, a variant of A* algorithm, is applied to mitigate the path angle change constraints introduced by grid-based graphs. With the Theta* and postsmoothing techniques, an obstacle-free, wind efficient, and constant above-ground-level flight plan can be quickly generated for sUAV operations in urban environments while meeting the lateral path angle constraints. The results showed that the path planning algorithm is efficient and can be finished within several seconds. With a proper choice of wind coefficient, the proposed path planning algorithm outperforms the multiple-shooting trajectory optimization method even in an obstacle-free environment. With the flexibility of incorporating other geo-related costs and computation efficiency, the proposed algorithm shows the potential for real-time flight path planning in complex urban environments.

ЗАБЕЗПЕЧЕННЯ ФУНКЦІОНАЛЬНО СТІЙКОГО РУХУ МАЛОГО АВТОНОМНОГО ЛІТАЛЬНОГО АПАРАТУ

The subjects of the study are the models and methods for providing functionally steady motion control of the small unmanned aerial vehicle (SUAV). The purpose of this work is the development of the method for providing functionally steady motion control of SUAV with a classical, minimally necessary composition of measuring sensors without hardware redundancy. The main task is to improve the existing diagnosing method of inertial navigation system (INS) model of SUAV, based on the combination of signals and the introduction of visual information from the onboard gyrostabilized camera, to implement the method of parrying emergency situation (ES) by applying for situational, synthetically created redundancy. The applied methods are the application of artificial system-hardware redundancy, signal-parametric approach, and the introduction of computer vision methods in the problem of angular and spatial positions calculating. As a result of the research, algorithmic dependencies of the orientation system signals were determined, which allowed to perform analysis and diagnostics with the subsequent restoration of the lost parameter due to hardware-system sensors redundancy. Conclusions. Developments in the field of providing functionally steady motion control systems for SUAV are in demand due to the need to increase the level of safety of SUAV flight upon incurrence of ES. At the same time, an obvious advantage is a work with minimal hardware redundancy of the sensors without the intervention of additional equipment. It is proved the possibility of the introduction of the optical systems (OS) as an additional source of geospatial information based on the use of visual information and computer vision methods with subsequent provision of artificial redundancy and implementation of majority calculation for providing functionally steady motion control of SUAV. It is demonstrated the practical application of the method in real conditions with the influence of artificially created ES. A functionally stable system will increase the effectiveness of existing SUAV, reduce the risk of loss of the apparatus during the flight

Low-cost Sensors Data Fusion for Small Size Unmanned Aerial Vehicles Navigation and Guidance

A new integrated navigation system designed for small size Unmanned Aerial Vehicles (UAVs) is presented. The proposed system is based on a number of low-cost avionics sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Sensors (VBS). The use of an Aircraft Dynamics Models (ADMs) to provide additional information to compensate for the shortcomings of Vision Based Navigation (VBN) and MEMS-IMU sensors in high-dynamics attitude determination tasks is also considered. Additionally, the research concentrates on the potential of carrier-phase GNSS for Attitude Determination (GAD) using interferometric techniques. The main objective is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance (position and attitude data) in all phases of flight of small UAVs, with a special focus on precision approach and landing, where VBN techniques can be fully exploited in a multi-sensor data fusion architecture. An Extended Kalman Filter (EKF) is developed to integrate the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UAV platform in real-time. Three different integrated navigation system architectures are implemented. The first architecture uses VBN at 20 Hz and GNSS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. The third fusion architecture uses GNSS based attitude values. The simulations are carried out on the AEROSONDE UAV performing high-dynamics manoeuvres repre-sentative of the UAV operational flight envelope. Simulation of the VBN-IMU-GNSS (VIG) integrated navigation system shows that the system can attain position, velocity and attitude accuracies complying with Category Two (CAT II) precision approach requirements. Simulation of the VBN-IMU-GNSS-ADM (VIGA) system also shows promising results, since the achieved attitude accuracy is higher using the ADM-VBN-IMU than using VBN-IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed. In the simulation of the third integrated navigation system, the VIG system is augmented by employing the GAD, forming the VIG-GAD (VIGGA) system architecture. The performances achieved with the VIG, VIGA and VIGGA integrated Navigation and Guidance System (NGS) are presented and are in line with the International Civil Aviation Organization (ICAO) precision approach requirements.

레이저포인터와 단일카메라를 이용한 거리측정 시스템

최근에 소형무인기(small UAV)에 대한 관심이 증대되고 있는데, 이는 소형무인기가 비용대비 효율적이고 사람의 접근이 어려운 재난 환경 등에 적합하기 때문이다. 이러한 소형무인기에서 거리측정을 통한 매핑(mapping)은 필수적인 기술이다. 기존의 무인시스템 연구에서 거리 측정 센서는 주로 레이저 센서와 스테레오 비전 센서를 많이 사용하였다. 레이저 센서는 정확도와 신뢰성이 우수하지만 대부분 고가의 장비이고 스테레오 비전 센서는 구현이 용이하지만 무게 측면에서 소형무인기에 탑재하여 사용하기에는 적합하지 않다. 본 논문에서는 레이저 포인터와 단일 카메라를 사용하여 저가의 거리측정기를 구성하는 방안을 소개한다. 제안한 시스템을 이용하여 거리를 측정하고 이로부터 맵을 구성하는 실험을 수행하였고 실제 데이터와 비교 분석하여 시스템의 신뢰성을 검증하였다. Recently, many unmanned aerial vehicle (UAV) studies have focused on small UAVs, because they are cost effective and suitable in dangerous indoor environments where human entry is limited. Map building through distance measurement is a key technology for the autonomous flight of small UAVs. In many researches for unmanned systems, distance could be measured by using laser range finders or stereo vision sensors. Even though a laser range finder provides accurate distance measurements, it has a disadvantage of high cost. Calculating the distance using a stereo vision sensor is straightforward. However, the sensor is large and heavy, which is not suitable for small UAVs with limited payload. This paper suggests a low-cost distance measurement system using a laser pointer and a monocular vision sensor. A method to measure distance using the suggested system is explained and some experiments on map building are conducted with these distance measurements. The experimental results are compared to the actual data and the reliability of the suggested system is verified.

System Identification of Small Unmanned Aerial Vehicle Flight Characteristics Issue I: Evaluation of Measurement Avionics and Analytical Methods

System Identification of Small Unmanned Aerial Vehicle Flight Characteristics Issue I: Evaluation of Measurement Avionics and Analytical Methods

Obstacle avoidance for small UAVs using monocular vision

PurposeThe purpose of this paper is to propose that the three‐dimensional information of obstacles should be identified to allow unmanned aerial vehicles (UAVs) to detect and avoid obstacles existing in their flight path.Design/methodology/approachFirst, the approximate outline of obstacles was detected using multi‐scale‐oriented patches (MOPS). At the same time, the spatial coordinates of feature points that exist in the internal outline of the obstacles were calculated through the scale‐invariant feature transform (SIFT) algorithm. Finally, the results from MOPS and the results from the SIFT algorithm were merged to show the three‐dimensional information of the obstacles.FindingsAs the method proposed in this paper reconstructs only the approximate outline of obstacles, a quick calculation can be done. Moreover, as the outline information is combined through SIFT feature points, detailed three‐dimensional information pertaining to the obstacles can be obtained.Practical implicationsThe proposed approach can be used efficiently in GPS‐denied environments such as certain indoor environments.Originality/valueFor the autonomous flight of small UAVs having a payload limit, this paper suggests a means of forming three‐dimensional information about obstacles with images obtained from a monocular camera.

Development and application of an integrated framework for small UAV flight control development

This paper presents an integrated framework for small Unmanned Aerial Vehicle (UAV) flight control development. The approach provides a systematic procedure for flight control design process with a set of design tools that enables control engineers to rapidly synthesize, analyze and validate a candidate controller design. A model-based environment integrated with control synthesis, off-line and real-time simulation is developed for flight control synthesis, analysis and testings. The effectiveness of the proposed integrated framework is demonstrated by applying the framework approach to a small UAV testbed. Software-in-the-loop, processor-in-the-loop and flight testings are conducted with the synthesized controller implemented. Closed-loop performance and robustness results obtained are presented.

Structural-parametric synthesis of the digital robust flight control system

The paper is devoted to the synthesis of the digital controller for a system with stochastic disturbances and incomplete measurements of the state vector. Then parametric robust optimization of obtained system is conducted to achieve stabilization and acceptable performance for nominal and parametrically disturbed plants using the same controller. Research is performed at the example of the small Unmanned Aerial Vehicle flight control system.