Autonomous functional configuration of a network robot system

We consider distributed systems of networked robots in which: (1) each robot includes sensing, acting and/or processing modular functionalities; and (2) robots can help each other by offering those functionalities. A functional configuration is any way to allocate and connect functionalities among the robots. An interesting feature of a system of this type is the possibility to use different functional configurations to make the same set of robots perform different tasks, or to perform the same task under different conditions. In this paper, we propose an approach to automatically generate at run time a functional configuration of a network robot system to perform a given task in a given environment, and to dynamically change this configuration in response to failures. Our approach is based on artificial intelligence planning techniques, and it is provably sound, complete and optimal. Moreover, our configuration planner can be combined with an action planner to deal with tasks that require sequences of configurations. We illustrate our approach on a specific type of network robot system, called Peis-Ecology, and show experiments in which a sequence of configurations is automatically generated and executed on real robots. These experiments demonstrate that our self-configuration approach can help the system to achieve greater autonomy, flexibility and robustness.