Generating an efficient hub graph for self-reconfiguration planning in modular robots

The self-reconfiguration planning has been considered as a major problem in the field of modular robots. In this paper, we propose a human-inspired map-based rout planning approach that speeds up the reconfiguration planning. In this method, the analogous to a map is a reconfiguration hub-graph which contains the major nodes of the reconfiguration graph. We propose an RRT-based approach to select these hubs such that they efficiently cover the full configuration graph. In a search for a path between two nodes of the graph, a pre-calculated optimal routing from a hub to another hub may be used. This method has been simulated for two different modular robots and the results show that, the time spent to find a solution is independent of the solution length. Experiments show 5 to 8 fold speed up in search time, while founded solutions are near-optimal. Also it has been shown that the configuration graph is scale free therefore the idea of using hubs is extendable to larger number of modules.