Self-organization by fuzzy clustering

New types of robot systems have recently been suggested based on the idea of distributed, collective intelligence analogous to biological systems. In this paper we investigate the relationship between fuzzy clustering (FC) and problems of self-organization in such systems, referred collectively as distributed robotic systems (DRS). The particular problem of self- organization in DRS prompts a reconsideration of the available FC techniques. Recent advances in FC are reviewed with the intent of adapting them to thy DRS problem. A `minimally biased' clustering algorithm producing a validity ranked hierarchy of partitions is applied to the self-organizing evolution of DRS. Two cases are considered: a bottom up self organization into increasing larger groups and a top down dispersion of a group to optimally cover a sensory field.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.