  Autonomous robots need to be able to handle uncertainties when deployed in
the real world. For the robot to be able to robustly work in such an
environment, it needs to be able to adapt both its architecture as well as its
task plan. Architecture adaptation and task plan adaptation are mutually
dependent, and therefore require the system to apply runtime architecture and
task plan co-adaptation. This work presents Metaplan, which makes use of models
of the robot and its environment, together with a PDDL planner to apply runtime
architecture and task plan co-adaptation. Metaplan is designed to be easily
reusable across different domains. Metaplan is shown to successfully perform
runtime architecture and task plan co-adaptation with a self-adaptive unmanned
underwater vehicle exemplar, and its reusability is demonstrated by applying it
to an unmanned ground vehicle.
