Coordinating Agile Systems Through the Model-based Execution of Temporal Plans

Agile autonomous systems are emerging, such as un-manned aerial vehicles (UAVs), that must robustly per-form tightly coordinated time-critical missions; for ex-ample, military surveillance or search-and-rescue sce-narios. In the space domain, execution of temporally flexible plans has provided an enabler for achieving the desired coordination and robustness. We address the challenge of extending plan execution to under-actuated systems that are controlled indirectly through the setting of continuous state variables. Our solution is a novel model-based executive that takes as input a temporally flexible state plan, specifying in-tended state evolutions, and dynamically generates a near-optimal control sequence. To achieve optimality and safety, the executive plans into the future, fram-ing planning as a disjunctive programming problem. To achieve robustness to disturbances and tractability, planning is folded within a receding horizon, continu-ous planning framework. Key to performance is a prob-lem reduction method based on constraint pruning. We benchmark performance through a suite of UAV scenar-ios using a hardware-in-the-loop testbed