Field report: Deployment of a fleet of drones for cloud exploration

Drones are commonly used for civil applications and are accessible to those with limited piloting skills in several scenarios. However, the deployment of a fleet in the context of scientific research can lead to complex situations that require an important preparation in terms of logistics, permission to fly from authorities, and coordination during the flights. This paper is a field report of the flight campaign held at the Barbados Island as part of the NEPHELAE project. The main objectives were to fly into trade wind cumulus clouds to understand the microphysical processes involved in their evolution, as well as to provide a proof of concept of sensor-based adaptive navigation patterns to optimize the data collection. After introducing the flight strategy and context of operation, the main challenges and the solutions to address them will be presented, to conclude with the evaluation of some technical evolution developed from these experiments.

Estimating wind using a quadrotor

The aim of this work is to estimate the average wind influencing a quadrotor drone only based on standard navigation sensors and equations of motion. It can be used in several situation, including atmospheric studies, trajectory planning under environmental constraints, or as a reference for studying flights in shear layer. For this purpose, a small quadrotor drone with spherical shape has been developed. Flight data are recorded from telemetry during indoor and outdoor flight tests and are post-processed. The proposed solution is based on a calibration procedure with global optimization to extract the drag model and a Kalman Filter for online estimation of the wind speed and direction. Finally, an on-board implementation of the real-time estimation is demonstrated with real flights in controlled indoor environment.

Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

A new nonlinear lifting line method for aerodynamic analysis and deep learning modeling of small unmanned aerial vehicles

In this work, a computationally efficient and high-precision nonlinear aerodynamic configuration analysis method is presented for both design optimization and mathematical modeling of small unmanned aerial vehicles. First, we have developed a novel nonlinear lifting line method which (a) provides very good match for the pre- and post-stall aerodynamic behavior in comparison to experiments and computationally intensive tools, (b) generates these results in order of magnitudes less time in comparison to computationally intensive methods such as computational fluid dynamics. This method is further extended to a complete configuration analysis tool that incorporates the effects of basic fuselage geometries. Moreover, a deep learning based surrogate model is developed using data generated by the new aerodynamic tool that can characterize the nonlinear aerodynamic performance of unmanned aerial vehicles. The major novel feature of this model is that it can predict the aerodynamic properties of unmanned aerial vehicle configurations by using only geometric parameters without the need for any special input data or pre-process phase as needed by other computational aerodynamic analysis tools. The obtained black-box function can calculate the performance of an unmanned aerial vehicle over a wide angle of attack range on the order of milliseconds, whereas computational fluid dynamics solutions take several days/weeks in a similar computational environment. The aerodynamic model predictions show an almost 1-1 coincidence with the numerical data even for configurations with different airfoils that are not used in model training. The developed model provides a highly capable aerodynamic solver for design optimization studies as demonstrated through an illustrative profile design example.

Investigation on aerodynamic characteristics of bionic membrane nano rotor

In this paper, the bionic membrane structure is introduced to improve the aerodynamic performance of nano rotor at the low Reynolds number. The aerodynamic characteristics of nano rotor made of hyperelastic material as membrane blades are studied. Firstly, based on the hyperelastic constitutive model, a finite element model of the rotor is established and compared with the results of the modal test to verify the accuracy of the model. Then the computational fluid dynamics model of membrane nano rotor is established which combined with the finite element model. The aerodynamic characteristics of the membrane rotor under hovering conditions are studied using fluid–structure interaction method. It is found that the calculation results matched well with the experiment results. The design of the structural parameters such as the membrane proportion, shape, and position of the membrane rotor is optimized. The influence of each parameter on the aerodynamic performance of the rotor is obtained. Under certain structural conditions, the performance can be effectively improved, which provides a new idea for the design of the nano rotor.

Never landing drone: Autonomous soaring of a unmanned aerial vehicle in front of a moving obstacle

Increasing endurance is a major challenge for battery-powered aerial vehicles. A method is presented which makes use of an updraft around obstacles to decrease the power consumption of a fixed-wing unmanned aerial vehicle. A soaring flight controller has been developed that can autonomously soar while the unmanned aerial vehicle keeps its relative position to that of a moving object. Multiple simulations have been performed to analyse the limitations of the soaring controller under different conditions. The effect of a change in wind velocity and updraft has been analysed. The simulations showed that an increase in updraft decreases the energy consumption of the flight controller. An increase in wind velocity results in a higher updraft requirement, while a decrease in the wind velocity requires less updraft. The simulations achieved sustained flight at 0% throttle. The controller has been validated experimentally using the updraft generated by a moving ship. The practical, autonomous tests reduced the average throttle down to 4.5% in front of a ship. The method presented in this study achieved successful hovering flight using an energy control module for longitudinal positioning.

User involvement before the development of an indoor RPAS for the creative industries

This paper presents user needs and preferences gathered prior to the development of an indoor remotely piloted air system. A literature review was carried out to analyse previous studies about the involvement of users in the design of indoor unmanned aerial vehicles. Subsequently, the results of these user needs obtained from three focus groups held in European countries (Belgium, Spain and United Kingdom) are presented here. Through a content analysis of the information obtained in the focus groups, 40 codes and 4 variables were defined and used to examine the differences between types of users and their previous experience with drones. The literature review gave support to the results obtained through users’ involvement in the features to be included in a new unmanned aerial vehicle. Non-parametric tests and qualitative comparative analysis were used to analyse the information gathered in the focus groups. The results revealed few differences between artists working in creative industries and drone operators working for the creative industries. These differences affected features such as detecting and avoiding obstacles, which requires the inclusion of sensors. In addition, previous experience with drones was found to be a sufficient condition to explain greater concerns over safety, ethical and security issues in indoor environments.

Vortex flow aerodynamics behind a symmetric airfoil at low angles of attack and Reynolds numbers

The low Reynolds number aerodynamics is important to investigate for micro air vehicle applications. The current paper covers numerical simulations to present the downstream development of the wake patterns and detailed analysis of the vortices generated at the downstream of NACA 0012 airfoil around the critical angle of attack where the instantaneous vortex patterns are oscillatory and differ from the mean vortex pattern for low Reynolds numbers ranging from 1000 to 4000. The instantaneous and mean aerodynamic forces, pressure and skin friction coefficients, and vorticity values are compared in addition to the path of the vortex centers, their longitudinal and lateral spacings, Kármán spacing ratios, and distortion ratios at the wake of the airfoil in regard to the different Reynolds numbers investigated. The streamwise and crosswise velocities of the vortex cores and relative velocities at different transverse locations are also discussed and presented in detail. The correlations between different non-dimensional numbers (St, Re, Ro) are obtained at these low Reynolds numbers investigated.

Hear-and-avoid for unmanned air vehicles using convolutional neural networks

To investigate how an unmanned air vehicle can detect manned aircraft with a single microphone, an audio data set is created in which unmanned air vehicle ego-sound and recorded aircraft sound are mixed together. A convolutional neural network is used to perform air traffic detection. Due to restrictions on flying unmanned air vehicles close to aircraft, the data set has to be artificially produced, so the unmanned air vehicle sound is captured separately from the aircraft sound. They are then mixed with unmanned air vehicle recordings, during which labels are given indicating whether the mixed recording contains aircraft audio or not. The model is a convolutional neural network that uses the features Mel frequency cepstral coefficient, spectrogram or Mel spectrogram as input. For each feature, the effect of unmanned air vehicle/aircraft amplitude ratio, the type of labeling, the window length and the addition of third party aircraft sound database recordings are explored. The results show that the best performance is achieved using the Mel spectrogram feature. The performance increases when the unmanned air vehicle/aircraft amplitude ratio is decreased, when the time window is increased or when the data set is extended with aircraft audio recordings from a third party sound database. Although the currently presented approach has a number of false positives and false negatives that is still too high for real-world application, this study indicates multiple paths forward that can lead to an interesting performance. Finally, the data set is provided as open access.

Assessment of 3D-printed span change structures applied to small unmanned aerial vehicles

An assessment of 3D-printed span-change structures is presented for determining suitability of the technology to small unmanned aerial vehicles. Materials and manufacturing technologies were used with an emphasis on near term applicability with design trades between the aerodynamic performance and structural response. Aerodynamic performance was assessed on three wind tunnel models varying span (432, 600, and 762 mm), wind speed (Reynolds numbers 18,000, 36,000, and 71,000), additive manufacturing print build plane and camber, quantifying structural response as the resulting shape during aerodynamic loading. Each model displayed increasing compliance as span increased with wing-tip displacement on the order of 50, 100, and 200 mm with various degrees of sweep and twist. Models generated excess lift at Re = 71,000 indicating potential flight demonstration of the technology with a lift to drag improvement of up to 97% at maximum wing extension.