Symbolic control applied to miniature quadcopter mission guidance

Being a fully algorithmic procedure, symbolic controller synthesis offers weighty advantages over other established synthesis procedures. In fact, the returned controllers provably enforce the given specification in the control loop making verification steps obsolete. However, the curse-of-dimensionality prevents this scheme from being applied to industrial problems. Applications to real experiments are indeed rare. In this note, we demonstrate how to utilize symbolic optimal control in order to control miniature quadcopters at the level of mission guidance. Specifically, a firefighting scenario using a Crazyflie 2.1 drone is considered, which involves reach-avoid and reach-and-stay control tasks. Furthermore, we present a runtime monitor, automatically derived from the synthesized symbolic controller. Based on the methodologies of plan recognition, this monitor observes the drone’s flightpath and infers the current controller mode. Thus, it is able to predict the upcoming manoeuvres of the drone.