ABSTRACT
A theoretical framework for design and analysis of flocking algorithms for mobile agents with obstacle-avoidance capabilities was developed by Olfati-Saber. The role of consensus algorithms in particle-based flocking is for an agent to achieve velocity matching with respect to its neighbors. A randomized algorithm for network design is proposed by Olfati-Saber, based on the random rewiring idea of Watts and Strogatz that led to the creation of their celebrated small-world model. The random rewiring of existing links of a network gives rise to considerably faster consensus algorithms. Multi-vehicle systems are an important category of networked systems due to their commercial and military applications. Markov processes establish an interesting connection between the information propagation speed in these two categories of algorithms proposed by computer scientists and control theorists. Flocks of mobile agents equipped with sensing and communication devices can serve as mobile sensor networks for massive distributed sensing in an environment.
