Showing papers by "Murat Bronz published in 2016"

Guidance algorithm for smooth trajectory tracking of a fixed wing UAV flying in wind flows

Abstract: This paper presents an algorithm for solving the problem of tracking smooth curves by a fixed wing unmanned aerial vehicle travelling with a constant airspeed and under a constant wind disturbance. The algorithm is based on the idea of following a guiding vector field which is constructed from the implicit function that describes the desired (possibly time-varying) trajectory. The output of the algorithm can be directly expressed in terms of the bank angle of the UAV in order to achieve coordinated turns. Furthermore, the algorithm can be tuned offline such that physical constraints of the UAV, e.g. the maximum bank angle, will not be violated in a neighborhood of the desired trajectory. We provide the corresponding theoretical convergence analysis and performance results from actual flights.

Flexible open architecture for UASs integration into the airspace: Paparazzi autopilot system

Abstract: Air safety authorities are forced to develop regulations for UAS due to incidents disturbing public safety and demands from UAS operators. Despite numerous studies from the FAA and EASA, none of them decided on a regulation for UASs. The reliability of the flight is considered to be one of the main obstacles for UAVs integration. This is not an easy topic considering the unknowns of the systems, environment and possible failures. We believe the flexibility required for such solutions calls for open architectures. More specifically, this paper shows how the use of the Paparazzi open source auto-pilot system can ease the integration of low altitude UAS. To ensure safety, this integration needs to be achieved through airspace management and UAS reliability. Preliminary airspace designs, e.g. Amazon's, identify different zones depending on the UAS capabilities, population density and altitude. Plus, national rules evolution push to cope with a variety of requirements. Open source and modular architectures are key to adapt to these requirements. From a UTM point of view, Paparazzi provide features to ease congestion management, such as dynamic geofencing, trajectory communication and collision avoidance. Concerning reliability, current regulations focus on flight constraints but might be expected to involve regulations on software and hardware components as well. In such case, the increased cost will be inevitable for the demands of certification. In the Paparazzi software case, parts of the code have been formally proved and stable versions have thousands of flight hours. Such heritage might ease the certification process for smaller companies. On top of its flexibility and reliability, Paparazzi offers a unique set of features, as an open source software, to achieve safe integration of low altitude UAS in the G airspace. To conclude this work, desirable new features and future work are discussed.

Aerodynamic Characterization of an Off-the-Shelf Aircraft via Flight Test and Numerical Simulation

Abstract: Characterization of an off-the-shelf small tailless aircraft with a wing span of 1:3m is presented. Mentioned aircraft is being used in several scientific measurement projects by authors, whereas the ight performance and quality such as endurance, and stability plays an important role on the measurement quality. Hence the main objective is to use the extracted and fine tuned aerodynamic and ight performance characteristics of the aircraft for a better flight control and mission planning during simulations and real flights. Aerodynamic characteristics are obtained through flight tests, numerical analyses, and some isolated ground experiments for the propulsion system. The comparison of different measurement and estimation techniques are discussed.

Fleets of enduring drones to probe atmospheric phenomena with clouds

Abstract: A full spatio-temporal four-dimensional characterization of the microphysics and dynamics of cloud formation including the onset of precipitation has never been reached. Such a characterization would yield a better understanding of clouds, e.g. to assess the dominant mixing mechanism and the main source of cloudy updraft dilution. It is the sampling strategy that matters: fully characterizing the evolution over time of the various parameters (P, T, 3D wind, liquid water content, aerosols...) within a cloud volume requires dense spatial sampling for durations of the order of one hour. A fleet of autonomous lightweight UAVs that coordinate themselves in real-time as an intelligent network can fulfill this purpose. The SkyScanner project targets the development of a fleet of autonomous UAVs to adaptively sample cumuli, so as to provide relevant data to address long standing questions in atmospheric science. It mixes basic researches and experimental developments, and gathers scientists in UAV conception, in optimal flight control, in intelligent cooperative behaviors, and of course atmospheric scientists. Two directions of researches are explored: optimal UAV conception and control, and optimal control of a fleet of UAVs. The design of UAVs for atmospheric science involves the satisfaction of trade-offs between payload, endurance, ease of deployment... A rational conception scheme that integrates the constraints to optimize a series of criteria, in particular energy consumption, would yield the definition of efficient UAVs. This requires a fine modeling of each involved sub-system and phenomenon, from the motor/propeller efficiency to the aerodynamics at small scale, including the flight control algorithms. The definition of mission profiles is also essential, considering the aerodynamics of clouds, to allow energy harvesting schemes that exploit thermals or gusts. The conception also integrates specific sensors, in particular wind sensor, for which classic technologies are challenged at the low speeds of lightweight UAVs. The overall control of the fleet so as to gather series of synchronized data in the cloud volume is a poorly informed and highly constrained adaptive sampling problem, in which the UAV motions must be defined to maximize the amount of gathered information and the mission duration. The overall approach casts the problem in a hierarchy of two modeling and decision stages. A macroscopic parametrized model of the cloud is built from the gathered data and exploited at the higher level by an operator, who sets information gathering goals. A subset of the UAV fleet is allocated to each goal, considering the current fleet state. These high level goals are handled by the lower level, which autonomously optimizes the selected UAVs trajectories using an on-line updated dense model of the variables of interest. Building the models involves Gaussian processes techniques (kriging) to fuse the gathered data with a generic cumulus conceptual model, the latter being defined from thorough statistics on realistic MesoNH cloud simulations. The model is exploited by a planner to generate trajectories that minimize the uncertainty in the map, while steering the vehicles within the air flows to save energy.

Electric Propulsion System Characterization through Experiments

Abstract: Electrical propulsion system characteristics are very important in UAV design, operation and control. This article presents the characterization of electric propulsion sets through experiments. A motor test bench have been build based on previous experience in order to improve the quality of the measurements. Moreover, the bench fits in a wind tunnel, allowing to perform a complete characterization over the full airspeed range of the considered mini and micro-UAVs. After recalling the general theoretical model of an electric motor, results from various combinations are presented.

Optimal design of long endurance mini UAVs for atmospheric measurement

Abstract: The work presented in this paper is carried out under the Skycanner project with the aim to study a fleet of coordinated mini-drones that will adaptively sample cumulus-type clouds, over periods of the order of one hour.

multi-dimensional Cloud-aERosol Exploratory Study using RPAS (mCERES): Bottom-up and top-down closure of aerosol-cloud interactions

Abstract: Clouds are omnipresent in earth's atmosphere and constitute an important role in regulating the radiative budget of the planet However, the response of clouds to climate change remains uncertain, in particular, with respect to aerosol-cloud interactions and feedback mechanisms between the biosphere and atmosphere Aerosol-cloud interactions and their feedbacks are the main themes of the European project FP7 BACCHUS (Impact of Biogenic versus Anthropogenic Emissions on Clouds and Climate: towards a Holistic Understanding) The National Center for Meteorological Research (CNRM-GAME, Toulouse, France) conducted airborne experiments in Cyprus and Ireland in March and August 2015 respectively to link ground-based and satellite observations Multiple RPAS (remotely piloted aircraft systems) were instrumented for a specific scientific focus to characterize the vertical distribution of aerosol, cloud microphysical properties, radiative fluxes, 3D wind vectors and meteorological state parameters Flights below and within clouds were coordinated with satellite overpasses to perform 'top-down' closure of cloud micro-physical properties Measurements of cloud condensation nuclei spectra at the ground-based site have been used to determine cloud microphyical properties using wind vectors and meteorological parameters measured by the RPAS at cloud base These derived cloud properties have been validated by in-situ RPAS measurements in the cloud and compared to those derived by the Suomi-NPP satellite In addition, RPAS profiles in Cyprus observed the layers of dust originating from the Arabian Peninsula and the Sahara Desert These profiles generally show a well-mixed boundary layer and compare well with ground-based LIDAR observations