Urban Swarm Navigation Exploiting sUAS Collaboration and Cognition

This paper focusses on one particular challenge of operating small Unmanned Aircraft Systems swarms in urban environments, namely advanced absolute and relative navigation methods for swarms and swarm members. The paper proposes novel absolute and relative pose and velocity estimation approach that extends conventional integrated navigation methods to include principles of cognition (i.e., appropriate and adapted actions based on perception and knowledge) and collaboration (i.e., improved ability to reason and interact based on information exchange and spatial distribution) between the swarm members. This paper outlines the underlying methodology, first simulation results, and the platform hardware components (three multi-copters and one ground station). It furthermore analyses and discusses the navigation performance using sUAS flight test data collected in an open-sky and simulations in an urban environment.