OVERVIEW OF THE METHODS FOR SELF-ORGANIZATION IN SWARM ROBOTICS

Self-organization is a common phenomenon observed in many natural and artificial systems. The overall coordinated behavior of the system is due to simple rules for interaction between its components. Thanks to these properties, self-organization plays a key role in swarm robotics, as it allows swarm coordination with minimal complexity of individual robots. This paper reviews the methods and tools for self-organization that are used in swarm robotics or are found in natural systems.

Adaptive Swarm Coordination and Formation Control

Swarm coordination and formation control designs focus on multi-agent dynamic system behavior and aim to achieve desired coordinated behavior or predefined geometric shape. They utilize techniques from the control theory and graph theory literature. On the other hand, adaptive control theory is concerned with uncertainties in the system dynamics, and has structured frameworks for various types of plant models. Therefore, in case there are uncertainties in the swarm dynamics, adaptive control methodologies can be utilized to achieve the desired coordinated behavior and there exist remarkable works in this direction. However, connection among swarm coordination, formation control, and adaptive control theory brings some restrictions as well as advantages. Hence adaptive swarm coordination and formation control has been developed in limited aspects. In this chapter, we review some existing works of the adaptive formation control literature along with non-adaptive ones, and discuss the advantages of application of adaptive control frameworks to swarm coordination and formation control.