This paper presents a software architecture for Unmanned aerial system Traffic Management (UTM). The work is framed within the U-space ecosystem, which is the European initiative for UTM in the civil airspace. We propose a system that focuses on providing the required services for automated decision-making during real-time threat management and conflict resolution, which is the main gap in current UTM solutions. Nonetheless, our software architecture follows an open-source design that is modular and flexible enough to accommodate additional U-space services in future developments. In its current implementation, our UTM solution is capable of tracking the aerial operations and monitoring the airspace in real time, in order to perform in-flight emergency management and tactical deconfliction. We show experimental results in order to demonstrate the UTM system working in a realistic simulation setup. For that, we performed our tests with the UTM system and the operators of the aerial aircraft located at remote locations with the consequent communication issues, and we showcased that the system was capable of managing in real time the conflicting events in two different use cases.
This paper addressed the challenge of exploring large, unknown, and unstructured industrial environments with an unmanned aerial vehicle (UAV). The resulting system combined well-known components and techniques with a new manoeuvre to use a low-cost 2D laser to measure a 3D structure. Our approach combined frontier-based exploration, the Lazy Theta* path planner, and a flyby sampling manoeuvre to create a 3D map of large scenarios. One of the novelties of our system is that all the algorithms relied on the multi-resolution of the octomap for the world representation. We used a Hardware-in-the-Loop (HitL) simulation environment to collect accurate measurements of the capability of the open-source system to run online and on-board the UAV in real-time. Our approach is compared to different reference heuristics under this simulation environment showing better performance in regards to the amount of explored space. With the proposed approach, the UAV is able to explore 93% of the search space under 30 min, generating a path without repetition that adjusts to the occupied space covering indoor locations, irregular structures, and suspended obstacles.
This paper presents a general framework for the definition and management of cooperative missions for multiple Unmanned Aircraft Systems (UAS) based on the Robot Operating System (ROS). This framework makes transparent the type of autopilot on-board and creates the state machines that control the behaviour of the different UAS from the specification of the multi-UAS mission. In addition, it integrates a virtual world generation tool to manage the information of the environment and visualize the geometrical objects of interest to properly follow the progress of the mission. The framework supports the coexistence of software-in-the-loop, hardware-inthe-loop and real UAS cooperating in the same arena, being a very useful testing tool for the developer of UAS advanced functionalities. To the best of our knowledge, it is the first framework which endows all these capabilities. The paper also includes simulations and real experiments which show the main features of the framework.
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