Modelling Assured Navigation of sUAS Swarms in Urban Environments

In this paper, the focus will be on the operation of swarms in one challenging environment: the urban environment. In this environment, sensor observations, such as camera images, laser point clouds, radar images and local beacon information may be utilized to get a better estimate of the absolute and relative position and velocity of the swarm and its members. In addition to swarms of sUAS, autonomous ground vehicles (AGVs) can be included as well as part of the team of unmanned vehicles. This paper describes a model that simulates swarms of sUAS, their sensors, and their motion, to evaluate swarm navigation integration approaches that enable assured (i.e., meeting a predefined set of performance and safety requirements) operation in an urban environment. The model is based on the Robotic Operating Systems 2 (ROS2), Gazebo, and Matlab and integrated with available urban 3D data (e.g., using OpenStreetMap or CityGML). An advantage of simulation in ROS2, is that the developed methods can be easily transferred to sUAS for flight test evaluations at a later point. The paper will describe the modelling frameworks and show some examples of their use.