Effective Planning Horizons for Robust Autonomy

Robust autonomy, in the sense of performing tasks in the face of dynamic changes to the environment, requires that an autonomous system be capable of responding appropriately to such changes. One such response is to effectively adapt the allocation of resources from planning to execution. By adapting the resource allocation between deliberation and execution, an autonomous system can produce shorter plans more frequently in environments with high levels of uncertainty, while producing longer, more complex plans when the environment offers the opportunity to successfully execute complex plans. In this paper we propose the idea of the “effective planning horizon” which adapts to environmental changes to bound the deliberation in an interleaved planning/execution system. The effective planning horizon is developed from an analysis of the advantages and disadvantages of three classic autonomous system architectures as feedback control systems. This leads to the development of an analytic model which suggests the use of maximizing the expected value of plans by adjusting the