Self-organization is one of the most important features observed in social, economic, ecological and biological systems. Distributed self-organizing systems are able to generate emergent global behaviors through local interactions between individuals without a centralized control. Such systems are supposed to be robust, self-repairable and highly adaptive. However, design of self-organizing systems is very challenging, particularly when the emerged global behaviors are required to be predictable or predictable. This talk introduces a morphogenetic approach to the self-organizing swarm robots using genetic and cellular mechanisms governing the biological morphogenesis. We demonstrate that morphogenetic self-organizing algorithms are able to autonomously generate patterns and surround moving targets without centralized control. Finally, morphogen based methods for self-organization of simplistic robots that do not have localization and orientation capabilities are presented.