Adaptive mission planning: the embedded OODA loop
David M. Lane · 2008
Abstract This paper proposes a novel tech-nique for autonomous mission plan recovery in order to increase operability of unmanned un-derwater vehicles. It combines the benefits of knowledge-based ontology representation, au-tonomous partial ordering plan repair and ro-bust mission execution. The approach is based on a combination of unrefinement and refine-ment stages on the plan-space domain in or-der to adapt declarative mission plans. It can handle uncertainty and action scheduling in or-der to maximize mission efficiency and minimise mission failures due to external unexpected fac-tors. Its performance is presented in a set of simulated scenarios for different concepts of op-erations for the underwater domain. The pa-per concludes by showing the results of a trial demonstration carried out on a real underwater platform. The results of this paper are readily applicable to land and air robotics.