Hierarchical Architecture of Swarm Command and Control Operations (HASCCO)

As the sophistication of unmanned aircraft systems (UAS) increases, so too does the strain they place on their operators. This strain is compounded when an operator is responsible for the control of multiple UAS working simultaneously, such as in a swarm. If an operator experiences too much mental strain, they may become overwhelmed and make costly errors which have catastrophic consequences. Current methods of swarm command and control are thoroughly researched though fail to address the impact on an operator(s) situation awareness. These architectures add complexity to an operation, while still relying solely on a human operator for command-and-control decision making on a macroscopic level. With the introduction of advanced neuromorphic computing hardware and 3
^rd
generation Artificial Intelligence systems, the strain placed on UAS operators could be delegated onto a hierarchical, autonomous UAS management entity. It would be responsible for interpreting commands given by the UAS operator, communicating between all assets in a swarm, delegating tasks to UAS within the swarm, making decisions based on the information available to the control system, and traveling with the swarm acting as a mobile pilot. This allows for an operator to take a more supervisory position, increasing their overall situation awareness, thus lowering mental workload. Neuromorphic technology allows our solution to be faster, lower power, scalable, generalized, and more autonomous when compared to architectures currently utilized.