A morphogenetic self-organization algorithm for swarm robotic systems using relative position information

Abstract

Inspired by the major principles of gene regulation and cellular interactions in multi-cellular development, this paper proposes a distributed self-organizing algorithm for multi-robot shape formation. In this approach, multiple robots are able to self-organize themselves into complex shapes driven by the dynamics of a gene regulatory network model. Particularly, no predefined global coordinate system is needed by building up a relative coordinate system through local interactions and limited communications among the robots. The target shape is represented by the non-uniform rational B-spline (NURBS) and embedded into the gene regulation model, analogous to the morphogen gradients in morphogenesis. Since the self-organization algorithm does not need absolute position information, the target shape can be formed anywhere within the environment based on the current location of the robots. Simulation and experimental results demonstrate that the proposed algorithm is effective for complex shape construction and robust to environmental changes and system failures.