Hybrid Flock - Formation Control Algorithms

Two prominent categories of algorithms for achieving coordinated multi-robot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. Although typically they are treated separately, we believe that a combination of flock and formation control represents a promising algorithmic solution. Such an algorithm could take advantage of a combination of characteristics of both categories that are best suited for a given situation. Therefore, in this work, we propose two distributed algorithms capable of gradually and reversibly shifting between flocking and formation behaviors using a single parameter \(\mathcal {W}\) . We evaluate them using both simulated and real robots with and without the presence of obstacles. We find that both algorithms successfully trade off flock density for formation error. Furthermore, leveraging a narrow passage experiment as an application case study, we demonstrate that an adaptive shift between flock and formation behavior, adopting a simple method to define \(\mathcal {W}\) in real-time using exclusively on-board resources, results in a statistically relevant reduction of traversing time in comparison to a non-adaptive formation control algorithm.