Automated planning as a new approach for the self-reconfiguration of mobile modular robots

We present a new approach to the solution of the self-reconfiguration problem for mobile modular robots (MMRs). The solution describes self-reconfiguration as a planning problem that can be tackled by an automated planner. In addition to the usage of the advanced domain-independent search heuristics within the planner, we introduce domain-specific heuristics into the domain description on a higher conceptual level. An explicit optimality measure is part of the given domain description. The planner can cope with difficult self-reconfigurations, e.g. involving building helper organisms. The abstract symbolic plan is executed by a behavior based robot controller, where each robot is seen as an agent that has access to local information only. The position which a robot takes in the final configuration is determined by swarm mechanisms during runtime. A coordination instance broadly monitors the self-reconfiguration. The feasibility and advantages of this approach compared to previous work on self-reconfiguration of MMRs is shown by planning and executing self-reconfiguration in simulation for several organism families with different reconfiguration complexities.