Spontaneous State Constraint Insertions to Operating Symbolic Controllers Combined with Runtime Assurance for Task Allocation in UAV Missions

The computation of symbolic controllers for non-linear plants is typically computationally expensive due to the well-known curse-of-dimensionality. In fact, those controllers must be computed before operating the closed loop. This note presents a method to modify symbolic controllers while they are operating the closed loop to avoid spontaneously inserted state obstacles. In addition, we utilize methods of plan recognition in combination with our new algorithm for providing a technique of decentralized runtime assurance for efficient task allocation and mission guidance in a multi-UAV setting. Promising results and the applicability of the found method is demonstrated by simulation and experiments with real physical systems.