UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication-support and other specific tasks. Their equipment and mission plan are carefully selected to minimize the carried load an overall resource consumption. Typically, several single task UAVs are dispatched to perform different missions. In certain cases, (part of) the geographical area of operation may be common to these single task missions (such as those supporting post-disaster recovery) and it may be more efficient to have multiple tasks carried out as part of a single UAV mission using common or even additional specialized equipment. In this paper, we propose and investigate a joint planning of multitask missions leveraging a fleet of UAVs equipped with a standard set of accessories enabling heterogeneous tasks. To this end, an optimization problem is formulated yielding the optimal joint planning and deriving the resulting quality of the delivered tasks. In addition, a heuristic solution is developed for large-scale environments to cope with the increased complexity of the optimization framework. The developed joint planning of multitask missions is applied to a specific post-disaster recovery scenario of a flooding in the San Francisco area. The results show the effectiveness of the proposed solutions and the potential savings in the number of UAVs needed to carry out all the tasks with the required level of quality.
As overviewed in @cite_10 , fleets of UAVs operating as distributed processing systems can be adopted for various monitoring tasks, including, e.g., surveillance, object detection, movement tracking, support to navigation. A prototype of UAV-based architecture for sensing operations has been described in @cite_18 . In our paper, we consider a conceptually similar UAV equipment of hardware and software modules.
@cite_18 @cite_10
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Future Unmanned Aircraft Systems (UASs) are expected to be nearly autonomous and composed of heterogeneous Unmanned Aerial Vehicles (UAVs). While most of the current research focuses on UAV avionics and control algorithms, ground task automation has come to the attention of researchers during the past few years. Ground task automation not only relieves human operators, but may also expand the UAS operation area, improve system coverage and enable operation in risky environments without posing a threat to humans. We propose a model to evaluate the coverage of a given UAS. We also compare different solutions for various modules of an automated battery replacement system for UAVs. In addition, we propose a ground station capable of swapping a UAV's batteries, followed by a discussion of prototype components and tests of some of the prototype modules. The proposed platform is well-suited for high-coverage requirements and is capable of handling a heterogeneous UAV fleet. Distributed Processing Systems are the ones that include multiple devices (which could be of many types, such as PC computers, mobile devices etc.) that have computational and communication capabilities. Their computational power is jointly used for collaborative processing of variety of tasks  and this processing is realized in distributed manner. UAV - Unmanned Aerial Vehicles (also called drones) gain significant attention over recent years. They have been employed to realize multiple tasks such as surveillance or environmental monitoring. First implementations were based on single UAV, later the potential of multiple UAVs collaborating in a team was noticed. Many applications were implemented in distributed manner, using multiple collaborative UAVs and the distributed processing systems principles. In this paper we survey the applications implemented over cooperative teams of UAVs that operate as distributed processing systems.