A membrane computing framework for self-reconfigurable robots

Abstract

Self-reconfigurable robots are built by modules which can move in relationship to each other, which allows the robot to change its physical form. Finding a sequence of module moves that reconfigures the robot from the initial configuration to the goal configuration is a hard task and many control algorithms have been proposed. In this paper, we present a novel method which combines a cluster-flow locomotion based on cellular automata together with a decentralized local representation of the spatial geometry based on membrane computing ideas. This new approach has been tested with computer simulations and real-world experiments performed with modular self-reconfigurable robots and represents a new point of view with respect other control methods found in the literature.