A generic operational simulation for early design civil unmanned aerial vehicles

Contemporary aerospace programmes often suffer from large cost overruns, delivery delays and inferior product quality. This is caused in part by poor predictive quality of the early design phase processes with regards to the operational environment of a product. This paper develops the idea of a generic operational simulation that can help designers to rigorously analyse and test their early product concepts. The simulation focusses on civil Unmanned Air Vehicle products and missions to keep the scope of work tractable. The research agenda is introduced along with ideas, initial results and future work. Designers specify details about their product, its environment and anticipated operational procedures. The simulation returns information that can help to estimate the value of the product using the value-driven design approach. Information will include recurring and non-recurring mission cost items. The research aim is to show that an operational simulation can improve early design concepts, thereby reducing delays and cost overruns. Moreover, a trade-off between mission fidelity and model generality is sought along with a generic ontology of civil Unmanned Air Vehicle missions and guidelines about capturing operational informatio

Asynchronous displays for multi-UV search tasks

Synchronous video has long been the preferred mode for controlling remote robots with other modes such as asynchronous control only used when unavoidable as in the case of interplanetary robotics. We identify two basic problems for controlling multiple robots using synchronous displays: operator overload and information fusion. Synchronous displays from multiple robots can easily overwhelm an operator who must search video for targets. If targets are plentiful, the operator will likely miss targets that enter and leave unattended views while dealing with others that were noticed. The related fusion problem arises because robots' multiple fields of view may overlap forcing the operator to reconcile different views from different perspectives and form an awareness of the environment by "piecing them together". We have conducted a series of experiments investigating the suitability of asynchronous displays for multi-UV search. Our first experiments involved static panoramas in which operators selected locations at which robots halted and panned their camera to capture a record of what could be seen from that location. A subsequent experiment investigated the hypothesis that the relative performance of the panoramic display would improve as the number of robots was increased causing greater overload and fusion problems. In a subsequent Image Queue system we used automated path planning and also automated the selection of imagery for presentation by choosing a greedy selection of non-overlapping views. A fourth set of experiments used the SUAVE display, an asynchronous variant of the picture-in-picture technique for video from multiple UAVs. The panoramic displays which addressed only the overload problem led to performance similar to synchronous video while the Image Queue and SUAVE displays which addressed fusion as well led to improved performance on a number of measures. In this paper we will review our experiences in designing and testing asynchronous displays and discuss challenges to their use including tracking dynamic targets. © 2012 by the American Institute of Aeronautics and Astronautics, Inc

Automatic system supporting multicopter swarms with manual guidance

[EN] Currently, there are some scenarios, such as search and rescue operations,where the deployment of manually guided swarms of UAVs can be necessary. In such cases, the pilot's commands are unknown a priori (unpredictable), meaning that the UAVs must respond in near real time to the movements of the leader UAV in order to maintain swarm consistency. In this paper we develop a protocol for the coordination of UAVs in a swarm where the swarm leader is controlled by a real pilot, and the other UAVs must follow it in real time to maintain swarm cohesion. We validate our solution using a realistic simulation software that we developed (ArduSim), testing flights with multiple numbers of UAVs and different swarm configurations. Simulation results show the validity of the proposed swarm coordination protocol, detailing the responsiveness limits of our solution, and finding the minimum distances between UAVs to avoid collisions.This work was partially supported by the "Programa Estatal de Investigation, Desarrollo e Innovation Orientada a Retos de la Sociedad, Proyecto TEC2014-52690-R", Spain, the "Universidad Laica Eloy Alfaro de Manabi," and the "Programa de Becas SENESCYT de la Republica del Ecuador."Fabra Collado, FJ.; Zamora, W.; Masanet, J.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2019). Automatic system supporting multicopter swarms with manual guidance. Computers & Electrical Engineering. 74:413-428. https://doi.org/10.1016/j.compeleceng.2019.01.0264134287

Smart environment monitoring through micro unmanned aerial vehicles

In recent years, the improvements of small-scale Unmanned Aerial Vehicles (UAVs) in terms of flight time, automatic control, and remote transmission are promoting the development of a wide range of practical applications. In aerial video surveillance, the monitoring of broad areas still has many challenges due to the achievement of different tasks in real-time, including mosaicking, change detection, and object detection. In this thesis work, a small-scale UAV based vision system to maintain regular surveillance over target areas is proposed. The system works in two modes. The first mode allows to monitor an area of interest by performing several flights. During the first flight, it creates an incremental geo-referenced mosaic of an area of interest and classifies all the known elements (e.g., persons) found on the ground by an improved Faster R-CNN architecture previously trained. In subsequent reconnaissance flights, the system searches for any changes (e.g., disappearance of persons) that may occur in the mosaic by a histogram equalization and RGB-Local Binary Pattern (RGB-LBP) based algorithm. If present, the mosaic is updated. The second mode, allows to perform a real-time classification by using, again, our improved Faster R-CNN model, useful for time-critical operations. Thanks to different design features, the system works in real-time and performs mosaicking and change detection tasks at low-altitude, thus allowing the classification even of small objects. The proposed system was tested by using the whole set of challenging video sequences contained in the UAV Mosaicking and Change Detection (UMCD) dataset and other public datasets. The evaluation of the system by well-known performance metrics has shown remarkable results in terms of mosaic creation and updating, as well as in terms of change detection and object detection

Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search

Target search with unmanned aerial vehicles (UAVs) is relevant problem to many scenarios, e.g., search and rescue (SaR). However, a key challenge is planning paths for maximal search efficiency given flight time constraints. To address this, we propose the Obstacle-aware Adaptive Informative Path Planning (OA-IPP) algorithm for target search in cluttered environments using UAVs. Our approach leverages a layered planning strategy using a Gaussian Process (GP)-based model of target occupancy to generate informative paths in continuous 3D space. Within this framework, we introduce an adaptive replanning scheme which allows us to trade off between information gain, field coverage, sensor performance, and collision avoidance for efficient target detection. Extensive simulations show that our OA-IPP method performs better than state-of-the-art planners, and we demonstrate its application in a realistic urban SaR scenario.Comment: Paper accepted for International Conference on Robotics and Automation (ICRA-2019) to be held at Montreal, Canad